NO322747B1 - Method and apparatus for predicting the performance of a drilling system in a given formation - Google Patents

Abstract

A method and apparatus for predicting the performance of a drilling system for drilling a wellbore (14) in a given formation, comprising generating a geology characteristic of the formation (24) per depth unit according to a prescribed geology model, obtaining specifications for proposed drilling equipment for use under drilling the wellbore (14), and predicting a drilling mechanic in response to the specifications as a function of the geology characteristics per depth unit according to a prescribed drilling mechanics model. In response to a predicted drilling mechanic, a controller (52) controls a parameter in the drilling of the wellbore (14). The specifications include at least one drill bit (22) specification of a recommended drill bit (22). Finally, the predicted drilling mechanics include at least one of the drill bit wear, mechanical efficiency, power, and operating parameters. A display is arranged to display the geology characteristics and predicted drilling mechanics per depth unit, comprising either a display monitor (60) or a printer (62).

Description

The present invention relates to drilling operations in drilling formations, and more particularly, methods and system apparatus for predicting the performance of drilling systems for a given formation.

From the very beginning of the oil and gas well drilling industry, as we know it, one of the biggest challenges has been the fact that it is impossible to really see what is going on in a borehole. It is the number of borehole conditions and/or events that can be of great importance in determining how to proceed with the operation. It is clear that all methods of attempting to sample such borehole conditions and/or events are indirect. To that extent, they are all less than ideal, and there is a constant effort in the industry to develop simpler and/or more accurate methods.

Generally, the approach in the art has been to focus on a particular wellbore condition or event and to develop a method to test that particular condition or event. E.g. US patent no. 5 305 836 describes a method by which wear on a drill bit that is in use can be modeled electronically, based on the lithology of the hole being drilled with that bit. This helps the drill operator decide when it is time to change the drill bit.

The process of deciding which type of drill bit to use in a given part of a formation has traditionally been based on very broad general considerations at best, and at worst, more a matter of technique and guesswork than of science.

Other examples could be given for this type of conditions and/or events and of known technology, reference can be made to GB 2 354 852 A.

Furthermore, there are several other conditions and/or events that could be useful to know. However, because they are less necessary, and in view of the priorities of developing better methods of testing the things that are more important, little or no attention has been given to methods of testing these other conditions.

It is therefore a purpose of the invention to provide an evaluation of various proposed drilling equipment before and during the actual drilling of a wellbore in a given formation, further for use in connection with a drilling program. Drilling equipment, in its selection and use, can be optimized for specific intervals of a wellbore in a given formation. The drilling mechanics models take advantage of the effects of progressive bit wear through changing lithology. Recommended operating parameters reflect the wear conditions for a drill bit in a specific lithology, and also take into account the operating limitations of a particular drilling rig being used. A printout or display of the geological characteristics and the predicted drilling mechanics per unit depth for a given formation provides key information that is very useful to a drilling operator, especially for use in optimizing the drilling process. The printout or display also advantageously produces an overview of expected drilling conditions and recommended operating parameters. This is achieved with the device according to the present invention as defined by the features stated in the claims.

The above and other information and advantages of the present invention will become more apparent after a detailed description of the best mode of carrying out the invention as given below, with reference to the drawing, in which Figure 1 illustrates a drilling system comprising an apparatus for predicting the performance of the drilling system to drill one or more well holes according to a prescribed drilling program in a given formation, Figure 2 illustrates a method for optimizing a drilling system and its use for drilling one or more well holes according to a prescribed drilling program in a given formation, where the method further comprises predicting the performance of the drilling system, Figure 3 illustrates geology and drilling mechanics models for use in embodiments of the drilling performance prediction method and apparatus of the present disclosure, Figures 4 (4a, 4b and 4c) illustrate an embodiment of a display of a predicted performance of a drilling system for a given formation according to progress the detail and the apparatus according to the present disclosure, and Figure 5 illustrates an embodiment of an exemplary display of parameters and real-time aspects of the drill prediction analysis and control system according to the present disclosure.

Reference is now made to Figure 1, where a drilling system 10 comprises a drilling rig 12 placed on top of a borehole 14. A logging tool 16 is carried by a sub 18, typically a drill collar, included in a drill string 20 and placed inside the borehole 14 A drill bit 22 is positioned at the lower end of the drill string 20, and cuts a borehole 14 through soil formations 24. Drilling mud 26 is pumped from the storage reservoir 28 near the wellhead 30, down an axial passageway (not illustrated) through the drill string 20, out of the openings in the drill bit 22 and back to the surface through the annulus 32. Metal casing 34 is placed in the drill hole 14 above the drill bit 22 to maintain the integrity of the upper part of the drill hole 14.

Reference is still made to figure 1. The annular space 32 between the drill stem 20, the sub 18, and the side walls 36 of the borehole 14 forms the return flow path for drilling mud. Mud is pumped from the mud tank near the wellhead 13 by the pumping system 38. The mud moves through the mud supply line 40 which is connected to a central passage that extends through the length of the drill string 20. Drilling mud is thus forced down through the drill string 20 and exits the borehole through openings in the drill bit 22 to cool and lubricate the drill bit and to carry cuttings produced during the drilling operation back to the surface. A fluid drain line 42 is connected from the annulus 32 at the wellhead to direct the return mud flow from the borehole 14 to the mud tank 28. Drilling mud is typically handled and processed by various devices (not shown) such as degassing units and circulation tanks to maintain a predetermined mud- viscosity and consistency.

The logging tool or instrument 16 may be any conventional logging instrument such as acoustic (sometimes called sonic), neutron, gamma ray, density, photoelectric, nuclear magnetic resonance, or any other conventional logging instrument, or combinations thereof, which may be used to measure lithology or porosity of the formation surrounding a soil borehole.

Since the logging instrument is inserted into the drill string 20 in Figure 1, the system is considered to be a measurement while drilling (MWD) system, i.e. it logs while the drilling process is underway. The log data can be stored in a conventional downhole recording device (not illustrated), which can be accessed at the soil surface when the drill string 20 is pulled out, or can be sent to the soil surface using telemetry such as the conventional mud pulse telemetry system. In all cases, the log data from the logging instrument 16 will eventually reach a processor 44 on the surface to allow the data to be processed for use according to the embodiments of the present disclosure as provided herein. That is, the processor 44 processes the log data as appropriate for use with the embodiments of the present disclosure.

In addition to MWD instrumentation, wire-log instrumentation can also be used. That is, wireline logging instrumentation can also be used to log the formation surrounding the borehole as a function of depth. With wireline instrumentation, a wireline truck (not shown) is typically located at the surface of a wellbore. A wire-logging instrument is suspended in the borehole by a logging cable that passes over a pulley, and a depth-measuring sleeve. As the logging instrument traverses the borehole, it logs the formation around the borehole as a function of depth. The log data is transmitted through a logging cable to a processor located at or near the logging truck to process the log data as appropriate for use with embodiments of the present disclosure. As with the MWD embodiment of Figure 1, the wireline instrumentation may include any conventional logging instrumentation that can be used to measure lithology and/or porosity of formations surrounding soil boreholes, e.g. such as an acoustic, neutron, gamma ray, density, photoelectric, nuclear magnetic resonance, or any other conventional logging instrument, or combinations thereof, that can be used to measure lithology.

Reference is again made to Figure 1, where an apparatus 50 is shown for predicting the performance of the drilling system 10 for drilling a series of boreholes, such as a borehole 14, in a given formation 24. The prediction apparatus 50 comprises a prescribed set of geological and drilling mechanics models, and further includes optimization, prediction and calibration modes for operation (which will be discussed further below with reference to Figure 3). The prediction apparatus 50 further comprises an apparatus 52 comprising any suitable conventionally available computer, controller, or data processing apparatus, which is further programmed to perform the methods and apparatus as described herein. The computer/controller 52 comprises at least one input for receiving input information and/or commands, e.g. from any input device or devices 58. The input device or devices 58 may comprise a keyboard, pointing device or the like, which further comprises a network interface or other communication interface to receive input information from a remote computer or database. Furthermore, the computer/controller 52 comprises at least one output for issuing information signals and/or equipment control commands. Output signals may be output to a display device 60 via signal lines 54 for use in generating a display of information contained in the output signals. The output signals can also be output to a printer device 62 for use in generating a printout 64 of information contained in the output signals. Information and/or control signals can also be sent out via signal lines 66 as required, e.g. to a remote device for use in controlling one or more various drilling operation parameters of the drilling rig 12, further discussed below. In other words, an appropriate device or means is provided on the drilling system, responsive to a predicted drilling mechanics output signal to control a parameter in a current drilling of a wellbore (or interval) with the drilling system. For example, the drilling system may include equipment such as one of the following types of controllable motors selected from a downhole motor 70, a top drive motor 72, or a rotary drilling motor 74, in which a given speed of a respective motor can be remotely controlled. The parameter may also include one or more of the following, selected from the group of bit weight, speed, mud pump flow rate, hydraulics, or other suitable drilling system control parameters.

The computer/controller 52 provides a means to generate a geological characterization of the formation per unit depth according to a prescribed geological model. The computer/controller 52 further arranges for the transmission of signals on the signal lines 54, 56, which represent the geological characteristics. The input device 58 can be used to enter specifications of proposed drilling equipment for use in the drilling of wellbore (or intervals of the wellbore). The specification includes at least a drill bit specification of a recommended drill bit. The computer/controller 52 further provides means for determining a predicted drilling mechanics in response to the specifications of the proposed drilling equipment as a function of the geology characteristic per unit depth, further according to a prescribed drilling mechanics model. The computer/controller 52 further arranges for sending out signals on the lines 54, 56 which represent the predicted drilling mechanics.

Computer/controller 52 is programmed to perform functions as described herein, using a programming technique well known in the art. In one embodiment, a computer-readable medium is included, wherein the computer-readable medium has a computer program stored thereon. The computer program for executing the computer/controller 52 is to predict the performance of a drilling system in drilling a wellbore of a given formation. The computer program includes instructions to generate a geological characteristic of the formation per unit depth according to a prescribed geological model, and to output signals representing the geological characteristic, wherein the geological characteristic comprises at least rock strength. The computer program also includes instructions for obtaining specifications of proposed drilling equipment for use in drilling the wellbore, where the specifications include at least a drill bit specification for a recommended drill bit. Finally, the program includes instructions for determining a predicted drilling mechanics in response to the specification of the proposed drilling equipment as a function of the geological characteristics per unit depth according to a prescribed drilling mechanics model, and sending signals representing the predicted drilling mechanics, wherein the predicted drilling mechanics includes at least the the following, selected from the group consisting of crown wear, mechanical efficiency, power and operating parameters. The programming of the computer program to implement the computer/controller 52 may further be accomplished using known programming techniques to implement the embodiments described and discussed herein. A geology for a given formation per depth unit can thus be generated, and in addition a predicted drilling mechanics performance of a drilling system can be determined. Furthermore, the drilling operation can advantageously be optimized in connection with a knowledge of a predicted performance thereof, as discussed further below.

In a preferred embodiment, the geological characteristic comprises at least rock strength. In an alternative embodiment, the geology characteristic may further comprise any one or more of the following, including logging data, lithology, porosity and shale plasticity.

As mentioned above, the input device 58 can be used to enter specifications of proposed drilling equipment for use in the drilling of a wellbore (or interval of wellbore). In a preferred embodiment, the specification comprises at least one drill bit specification for a recommended drill bit. In an alternative embodiment, the specification may also include one or more specifications of the following equipment which may include borehole motor, top drive motor, rotary drilling motor, mud system, and mud pump. Corresponding specifications may include a maximum torque output, a type of mud, or a mud pump output rating, for example, that would be appropriate in conjunction with a particular drilling rig.

In a preferred embodiment, the predicted drilling mechanics comprises at least one of the following drilling mechanics selected from the group consisting of bit wear, mechanical efficiency, power, and operating parameters. In another embodiment, the operating parameters may include crown weight, rotating rpm (rotations per minute), cost, penetration rate, and torque, which will be discussed further below. The rate of penetration also includes an instantaneous rate of penetration (ROP) and an average rate of penetration (ROP-AVG).

Reference is now made to Figure 2. A flow diagram illustrating a method of drilling a series of well holes in a given formation using the apparatus 50 to predict the performance of the drilling system will now be discussed. The procedure is to optimize both the drilling system and the use of a drilling program, further in connection with the drilling of one or more well holes (or intervals of a well hole) in a given formation. In step 100, the method comprises the beginning of a particular drilling program or a continuation of a drilling program for a given formation. In connection with a continuation of the drilling program, it may be that the drilling program has been interrupted for one reason or another, e.g. due to equipment failure or downtime, and as a result, the drilling program is only partially completed. After repair or replacement of failed equipment, the method according to the present invention can again be started at step 100. Note that the method according to the present description can be implemented at any point in a given drilling program to optimize the particular drilling system and its use, preferably implemented from the beginning of a given drilling program. In step 102, a predicted drilling performance of a drilling system for drilling a wellbore in the given formation is generated according to the present description. Additionally, the predicted drilling performance for drilling a given well is generated according to a prescribed set of geology and drilling mechanics prediction models using at least one of the following modes selected from a group consisting of an optimization mode and a prediction mode. In other words, in generating the predicted drilling performance of the drilling system, either optimization mode and/or prediction mode can be used. The predicted drilling performance includes predicted drilling mechanics measurements. Optimization mode and prediction mode will be discussed further below, in connection with Figure 3.

In step 104, the drilling operator makes a determination as to how far to obtain true drilling mechanics measurements during the drilling of the given wellbore (or interval of a wellbore). In step 106, if relevant drilling mechanics measurements (eg, operating parameters) are to be obtained, the given wellbore (or interval) is drilled with the drilling system using the predicted drilling performance as a guide. Furthermore, in step 106, during the drilling of the wellbore (or interval) relevant drilling mechanics measurements are taken. Alternatively, if the decision is not to obtain measurement of operational parameters during the drilling of a given wellbore (or interval of a wellbore), the method proceeds to step 132, which will be discussed further below.

In step 108, the predicted drilling performance is compared to the actual drilling performance, using a calibration mode of operation, which calibration mode will be discussed further herein with reference to Figure 3. In comparison, actual drilling mechanics measurements are compared to predicted drilling mechanics measurements. The comparison process preferably includes superimposing a plot of the actual performance over the predicted performance (or vice versa) to visually determine deviations between the actual and predicted performances. The comparison can also be implemented using a computer to compare appropriate data.

Reference is now made to step 110 of Figure 2. Step 110 includes a question about the extent to which the prescribed geology and drilling mechanics models are optimized for the specific geology and drilling system. In other words, if the models are optimized for the specific geology and the specific drilling system, the comparison of the actual drilling mechanics measurements with the predicted drilling mechanics measurements is acceptable. The procedure then proceeds to step 112, in connection with the drilling of a subsequent well hole in the series of well holes. On the other hand, if the models are not optimized for the specific geology and drilling system, the method proceeds from step 110 to step 114. If the comparison of the actual drilling mechanics measurements with the predicted drilling mechanics measurements in step 108 is not acceptable, at least one of the geology and drilling mechanics models fine-tuned using the calibration mode of the operation. In step 114, the geology and drilling mechanics models are fine-tuned (in whole or in part) using the calibration mode. Using the calibration mode, all or some of the geology and drilling mechanics models are fine-tuned as appropriate, further as determined from the comparison of actual versus predicted drilling performance. After fine-tuning the models in step 114, the method proceeds to step 112, in connection with the drilling of a later well in the series of wells.

In step 112, the actual drilling performance of the current well is compared to a performance of a previous well (or previous wells). Such a comparison makes it possible to determine whether any improvements in performance have occurred. For example, the comparison may show that the current well was drilled for 18 days versus 20 days for previous wells. After step 112, in step 116, a question is raised as to whether the geology and drilling mechanics models were optimized on a previous well or wells. If the models were optimized, the method proceeds to step 118. Alternatively, if the models were not optimized on a previous well or wells, the method proceeds to step 120.

In step 118, the value of the optimized operating parameters of the drilling performance is documented. Further, the value of the optimized operating parameter on the drilling performance is documented and/or recorded in any suitable manner for easy access and retrieval. Documentation and/or registration may include, for example, a progress report, a data file or database. Step 118 thus facilitates the capture of the value of optimizing operating parameters on drilling performance. Examples of the value of optimization can include different benefits, e.g. economic benefits of optimized drilling, fewer trips to the particular field being drilled, less time required to drill a well, or any other appropriate value metrics. To illustrate further with a simple example, assume that an offshore drilling program costs in the order of USD 150,000 per day to run. A saving or reduction of 2 days per well (as a result of optimizing the drilling system and its use) would equate to a saving of USD 300,000 per well. For a drilling program of 30 wells, the combined savings resulting from optimization could potentially be as much as USD 9,000,000 for the given drilling program.

In step 120, it is examined whether design changes have been made to one or more previous wells. If design changes were made, the method proceeds to step 122.1 step 122, similarly to step 118, the value of design changes on drilling performance is documented. That is, the value of the design changes on drilling performance is documented and/or recorded in any suitable way for easy access and retrieval. Documentation and/or registration may include e.g. a progress report, a data file, or a database. Step 122 thus facilitates capturing the value of design changes on drilling performance. Alternatively, if no design changes were made to previous wells, then the method proceeds to step 124.

In step 124, an investigation is made as to whether the drilling system is optimized for the specific geology. For example, in a running well, a particular drilling equipment limitation can have a strong effect on drilling performance if the drilling system is not optimized for the specific geology. For example, if a mud pump is inadequate for a given geology, the resulting hydraulics may also be inadequate for cleaning the hole, thus adversely affecting the drilling performance of the drilling system for that specific geology. If the drilling system is not optimized for the specific geology, the method proceeds to step 126, otherwise the method continues to step 128.1 step 126, appropriate design changes are implemented or made to the drilling system. The design changes may include replacement of equipment, retrofitting and/or modification, or other design changes deemed appropriate for the specific geology. The drilling system equipment and its use can thus be optimized for drilling in the given geology. The process then continues to step 128.

In step 128, an investigation is made as to whether the last well in the drilling program has been drilled. If the last well has been drilled, the method ends at step 130. If the last well has not yet been drilled, the method returns to step 102, and the process continues as discussed above.

In step 132, if the drilling system operating parameters are not to be achieved, the given wellbore (or interval) is drilled with the drilling system using the predicted drilling performance as a guide, without measurements being taken. In step 132, during the drilling of the wellbore (or interval), no drilling mechanics measurements are taken. After completion of the drilling of the running well (or interval) in step 132, the method may proceed to step 128, and the process continues as discussed above.

The method and apparatus according to the present description advantageously enable an optimization of a drilling system and its use in a drilling program to be achieved early in a given drilling program. For example, with the present method and apparatus, an optimization could be achieved within a few wells of a thirty well program, while without the present method and apparatus, optimization could not be achieved until the fifteenth well of the thirty well program. The present method further facilitates the execution of appropriate improvements early in the drilling program. Economic benefits resulting from the improvements made early in the drilling program are advantageously multiplied by the number of wells that remain to be drilled in the drilling program. As a result, significant and substantial savings for a company commissioning the drilling program can be advantageously achieved. Measurements can be made during the drilling of each well hole, throughout the entire drilling program, using the present method and apparatus for the purpose of verifying that the special drilling system equipment is optimally used. In addition, drilling system equipment performance can be more easily monitored with the method and apparatus of the present disclosure, further identifying potential adverse conditions before they actually occur.

Reference is now made to figure 3, where a model of a total drilling system is produced by the prediction models 140. The prediction models include geology models 142 and drilling mechanics models 144, further according to the present method and apparatus. Figure 3 illustrates an overview of the different prediction models 140 and how they are interconnected. The prediction models 140 are stored in and executed by the computer/controller 52 of Figure 1, as further discussed herein.

The geology models 142 comprise a lithology model 146, a rock strength model 148, and a shale plasticity model 150. The lithology models preferably comprise a lithology model as described in US patent 6,044,327, issued March 28, 2000, entitled "Method for Quantifying the Lithologic Composition of Formations Surrounding Earth Boreho-les", and incorporated herein by reference. The lithology models provide a method for quantifying lithology component fractions of a given formation, including lithology and porosity. The lithology model uses any lithology or porosity-sensitive logging tool, eg, including nuclear magnetic resonance, photoelectric, neutron density, sonic, gamma ray, and spectral gamma ray. The lithology model further provides an improved multi-component analysis. For example, in the lithology column of Figure 4, at 575 feet depth, four components are shown comprising sandstone, shale, dolomite, and shale. Components can be weighted to a particular log or group of logs. The lithology model confirms that certain logs are better than others for resolving a given lithology component. For example, it is well known that the gamma ray log is generally the best shale indicator. A streak of coal may be clearly resolved by a neutron log, but completely missed by a sonic log. Weighting factors are applied so that a given lithology is resolved by the log or group of logs that can resolve it most accurately. In addition, the lithology models allow the maximum concentration of any lithology component to vary from 0 to 100%, thereby allowing calibration of the models to a core analysis. The lithology models also allow limited areas of existence for each lithology component, which can further be based on a core analysis. The lithology models may also include any other suitable models for predicting lithology and porosity.

The rock strength model 148 preferably comprises a rock strength model as described in US Patent 5,767,399, issued June 16, 1998, entitled "Method of Assaying Compressive Strength of Rock", and incorporated herein by reference. The rock strength models provide a method for predicting confining stress and rock strength.

The shale plasticity model 150 preferably comprises a shale plasticity model as described in US patent 6,052,649, issued April 18, 2000, entitled "Method and Apparatus for Quantifying Shale Plasticity from Well Logs", and incorporated herein by reference. The shale plasticity model provides a method for quantifying shale plasticity in a given formation. The shale plasticity model may also include any other suitable models for predicting shale plasticity. The geology models thus provide for the generation of a model of the special geological application of a given formation.

The drilling mechanics models 144 comprise a mechanical efficiency model 152, a hole cleaning efficiency model 154, a drill bit wear model 156, and a penetration rate model 158, mechanical efficiency model 152 preferably comprises a mechanical efficiency model as described in concurrent patent application S/N 09/048 360, filed March 26, 1998, entitled "Method of Assaying Downhole Occurrences and Conditions" and incorporated herein by reference. The mechanical efficiency model produces a method for determining the mechanical efficiency of the drill bit. In the mechanical efficiency model, mechanical efficiency is defined as the percentage of torque that cuts. The remaining torque is consumed as friction. The mechanical efficiency model a) reflects 3-D bit geometry, b) is associated with cutting torque, c) considers the effects of operational constraints, and d) makes use of a torque and drag analysis.

With respect to the hole cleaning efficiency (HCE) model 154, the model takes into account the type of drilling mud, hydraulics, lithology and shale plasticity. The hole cleaning efficiency model is a measure of an efficiency of drilling mud and hydraulics. If the hole cleaning efficiency is low, unremoved or slowly removed cuttings will have an adverse effect on the drilling mechanics.

The bit wear model 156 preferably includes a wear model as described in US Patent 5,794,720, issued August 18, 1998, entitled "Method of Assaying Downhole Occurrences and Conditions", and incorporated herein by reference. The bit wear model provides a method for determining bit wear, i.e. predicting bit life and formation abrasiveness. Furthermore, the bit wear model is used to provide a work class for a given drill bit.

The penetration rate model 158 preferably comprises a penetration rate model as described in US Patent 5,704,436, issued January 16, 1998, entitled "Method of Regulating Drilling Conditions Applied to a Well Bit", and incorporated herein by reference. The penetration rate model provides a method to optimize operating parameters and to predict penetration rate for the drill bit and drilling system. The ROP model provides one or more of the following: maximization of a penetration rate, establishment of a power limit to avoid shock damage to the crown, respect of all operational constraints, optimization of operational parameters, and minimization of crown-induced vibrations.

The drilling mechanics models 144 as described herein provide for the generation of a comprehensive model of the particular drilling system being used or proposed for use in the drilling of a wellbore, intervals of a wellbore, or a series of boreholes in a given borehole operation. The drilling mechanics models 144 further allow the generation of a drill bit mechanics performance prediction of the drilling system in a given geology. A comparison of actual performance with predicted performance can be used for history fitting of the drilling mechanics models, which may be necessary for optimization of the respective drilling mechanics models.

Reference is still made to figure 3. The present method and apparatus comprise several operating modes. The modes of operation include an optimization mode, a prediction mode and a calibration mode. For the various modes of operation, predicted economics can be included to provide a measure of the number of fewer days per well that can be achieved when a drilling system is optimized using the methods and apparatus of the present invention.

Optimization mode

In optimization mode, the purpose is to optimize the operating parameters of the drilling system. The optimization criteria include 1) maximizing penetration rate, 2) avoiding impact damage to the crown, 3) respecting all operational constraints, and 4) minimizing crown-induced vibrations.

In optimization mode, the lithology model 146 receives data from porosity logs, lithology logs, and/or mud logs at input 160. The porosity or lithology logs may include nuclear magnetic resonance (NMR), photoelectric, neutron density, sonic, gamma ray, and spectral gamma ray, and any other log which is sensitive to porosity or lithology. The mud logs are used to identify non-shale lithology components. In response to the log inputs, the lithology model 146 provides a measure of lithology and porosity of the given formation per unit depth on the output 162. When it relates to lithology, the output 162 preferably comprises a volume fraction of each lithology component of the formation per unit depth. When it comes to porosity, the output 162 preferably comprises a volume fraction of pore space inside the rock in the formation per unit depth. The lithology measure of porosity at the outlet 162 is input to the rock strength model 148, shale plasticity model 150, mechanical efficiency model 152, hole cleaning efficiency model 154, crown wear model 162, and penetration rate model 158.

In the case of rock strength model 148, in addition to receiving a measure of lithology and porosity output 162, rock strength model 148 also receives mud weight and pore pressure data at input 164. The mud weight is used to calculate overbalance. The pore pressure is used to calculate overbalance and alternatively, design overbalance can be used to calculate pore pressure. In response to the inputs, the rock strength model 148 produces a measure of confining stress and rock strength of the given formation per unit depth at the output 166. More specifically, the rock strength model produces a measure of overbalance, effective pore pressure, confining stress, unconfined rock strength, and limited rock strength. Overbalance is defined as mud weight minus pore pressure. Effective pore pressure is similar to pore pressure, but also reflects permeability reduction in shale and low porosity non-shale. Confining stress is a calculation of in situ computational stress of rock. Unconfined rock strength is rock strength at the surface of the earth. Finally, confined rock strength is rock strength under in situ confining stress conditions. As shown, the rock strength output 166 is input to mechanical efficiency model 152, crown wear model 162, and penetration rate model 158.

With respect to mechanical efficiency model 152, in addition to receiving the lithology and porosity output 162 and confining stress and rock strength output 166, mechanical efficiency model 152 also receives input data regarding operational constraints, 3-D crown model, and torque and drag, all relative to the drilling system, on input 168. Operating limitations may include maximum torque, maximum weight on crown (WOB), maximum and minimum RPM, and maximum penetration rate. In particular, in terms of mechanical efficiency, the operational constraints on the drilling system include maximum torque, maximum weight on bit (WOB), minimum RPM and maximum penetration rate. The operating constraints limit the amount of optimization that can be achieved with a particular drilling system. Furthermore, with regard to evaluating the impact of operational limitations on mechanical efficiency, although not all limitations affect both mechanical efficiency and power, it is necessary to know all the limitations in order to quantify the effects of those limitations that have an effect on either mechanical efficiency or power. The 3-D crown model input includes a crown work class and a moment WOB signature. Finally, the torque and drag analyzes include a direction proposal, casing and drill string geometry, mud weight and flow rate, friction factors, or torque and drag measurements. The torque and drag analyzes are necessary to determine how much surface torque is actually transferred to the crown. Alternatively, bottom and bottom torque measurements can be used instead of torque and drag analysis. In addition, near bit measurements from a measurement while drilling (MWD) system could also be used instead of torque and drag analysis. In response to the input information, mechanical efficiency model 152 will produce a measure of mechanical efficiency, constraint analysis, predicted torque, and optimum weight on bit (WOB) for the drilling system in a given formation per unit depth 170. More specifically, mechanical efficiency model 152 will provide a measure of total torque, shear torque, friction torque, mechanical efficiency, a constraint analysis, and optimal WOB. The total torque represents a total torque applied to the drill bit. The shear torque represents the shear component of the total torque. The frictional torque is the frictional component of the total torque. With the mechanical efficiency model 152, the mechanical efficiency is defined as the percentage of the total torque that cuts. The constraint analysis quantifies the reduction in mechanical efficiency from a theoretical maximum value due to each operational constraint. Finally, an optimal WOB is determined, for which WOB maximizes the penetration rate while respecting all operational constraints. The optimal WOB is used by the penetration rate model 158 to calculate an optimal RPM. Furthermore, mechanical efficiency model 152 also uses a measure of drill bit wear from a previous iteration as input, which will be further described below in connection with the drill bit wear model.

With respect to the crown model 156, it receives inputs from the lithology model via output 162, the rock strength model via output 166, and the mechanical efficiency model via output 170. In addition, the crown model 156 further receives 3-D crown model data at input 172. The 3-D crown model input includes a krone work class and a moment WOB signature. In response to the inputs of lithology, porosity, mechanical efficiency, rock strength, and 3-D crown model, the crown wear model 156 produces a measure of specific energy, total work, formation abrasiveness, and crown wear relative to the crown in a given formation per unit depth, on output 174. The specific energy is the total energy supplied by the drill bit, which corresponds to the bit force divided by the bit's cross-sectional area. The overall work performed by the drill bit reflects both the rock strength and mechanical efficiency. The formation abrasiveness measure models an accelerated wear due to the formation's abrasiveness. Finally, the measure of crown wear corresponds to a state of wear associated with crown axial contact area and mechanical efficiency. In addition to output 174, crown wear model 156 further comprises provision of a measure of crown wear from a previous iteration to mechanical efficiency model 152 on output 176, where mechanical efficiency model 152 further uses the crown wear measure from a previous iteration in the calculation of its mechanical efficiency output data on output 170.

Before discussing the penetration rate model 158, one first returns to the shale plasticity model 150. As shown in Figure 3, the shale plasticity model 150 receives input from the lithology model. Specifically, shale volume is derived from the lithology model 146. In addition to receiving lithology and porosity output 162, the shale plasticity model 150 further receives log data from prescribed well logs on input 178, where the well logs include any log sensitive to the type of clay, clay water content, and clay volume. Such logs may include nuclear magnetic resonance (NMR), neutron density, sonic density, spectral gamma rays, gamma rays, and cation exchange capacity (CEC). In response to the inputs, the shale plasticity model 150 produces a measure of shale plasticity in the formation per unit depth, at the output 180. In particular, the shale plasticity model 150 produces a measure of normalized clay type, normalized clay water content, normalized clay volume, and shale plasticity. The normalized clay type identifies a maximum concentration of smectites, where smectite is the clay type most likely to cause clay reswelling. The normalized clay water content identifies the water content where a maximum shale plasticity occurs. The normalized clay volume identifies the range of clay volume where plastic behavior can occur. Finally, shale plasticity is a weighted average of the normalized clay properties, and reflects an overall plasticity.

Referring to the hole cleaning efficiency model 154, the model 154 receives a shale plasticity input from the shale plasticity model 150 and a lithology input from the lithology model 146. In addition to receiving the lithology model output 162 and the shale plasticity model output 180, the hole cleaning efficiency model 154 receives hydraulic and drilling fluid data on the input 182. In particular, hydraulic input may include a standard measure of hydraulic efficiency, such as hydraulic horsepower per square inch of bit diameter. In addition, the drilling fluid type may include water-based mud, oil-based mud, polymer, or other known fluid types. In response to the input, the cleaning efficiency model produces a measure of a predicted hole cleaning efficiency of the bit and drilling system in drilling a well hole (or interval) in the formation per unit depth, at the output 184. The hole cleaning efficiency is defined as the actual over the predicted penetration rate. While the other drilling mechanics models assume perfect hole cleaning, the hole cleaning efficiency (HCE) model is a measure of correction to the penetration rate prediction to compensate for hole cleaning deviating from ideal behavior. The measure of hole cleaning efficiency (HCE) thus reflects the effects of lithology, shale plasticity, hydraulics, and drilling fluid type and penetration rate.

Referring to penetration rate model 158, it receives mechanical efficiency, predicted torque, and optimum WOB via output 170 of mechanical efficiency model 152. Model 158 further receives bit wear via output 174 of bit wear model 156, rock strength via output 166 of rock strength model 148, and predicted HCE via output 184 of the HCE model 154. In addition, the penetration rate model 158 receives further operating limitation information on input 186. In particular, the operating limitations include maximum torque, maximum weight on crown (WOB), maximum and minimum RPM, and maximum penetration rate. Furthermore, with regard to evaluating the effects of the operational limitations on power, while not all limitations affect both mechanical efficiency and power, it is necessary to know all the limitations in order to quantify the effects of those limitations that have an effect on either mechanical efficiency or power. In response to the inputs, the penetration rate model 158 produces a power level analysis, a constraint analysis, and, in addition, a measure of optimal RPM, penetration rate, economics for the bit and the drilling system in drilling a wellbore (or interval) in the formation per unit depth, at the output 188. More in particular, the power level analysis includes a determination of the maximum power limit. The maximum power limit maximizes the rate of penetration without causing shock damage to the crown. The operating power level may be less than the maximum power level due to operating limitations. The limitation analysis includes quantification of the reduction in operational power level from the maximum power limit due to each operational limitation. The optimal RPM is the RPM that maximizes the penetration rate while respecting all operating constraints. The penetration rate is the predicted penetration rate at optimal WOB and optimal RPM. Finally, the economies can include the industry standard cost per foot analysis.

Prediction mode

In prediction mode, the goal or intent is to predict drilling performance with user-specified operating parameters that are not necessarily optimal. Operating restrictions do not apply in this mode. Prediction mode is essentially similar to optimization mode, however, with the exceptions of mechanical efficiency model 152, crown wear model 156, and penetration rate model 158, further as explained below, hole cleaning efficiency model 154 is the same for both optimization and prediction modes, since hole cleaning efficiency is independent of the mechanical operating parameters (ie user-specified WOB and user-specified

rpm).

With respect to mechanical efficiency model 152, in prediction mode, in addition to receiving lithology and porosity output 162 and confining stress and rock strength output 166, mechanical efficiency model 152 receives further input data regarding user-specified operating parameters and a 3-D crown model, related to the drilling system, on input 168. The user-specified operating parameters for the drilling system may include a user-specified weight on the bit (WOB), and a user-specified RPM. This option is used to evaluate "what if" scenarios. The 3-D crown model input includes a crown work class and a torque WOB signature. In response to the input, mechanical efficiency model 152 produces a measure of mechanical efficiency for the drilling system in the given formation per unit depth, at output 170. More specifically, mechanical efficiency 152 produces a measure of total torque, cutting torque, friction torque, and mechanical efficiency. The total torque represents the total torque supplied to the drill bit. In prediction mode, the total torque equals the user-specified weight of the crown. The cutting torque represents the cutting component of the total torque on the crown. The friction torque is the friction component of the total torque on the drill bit.

With the mechanical efficiency model 152, the mechanical efficiency is defined as the percentage of the total torque that cuts. Prediction mode can also include an analysis of mechanical efficiency by range, i.e. the range of mechanical efficiency in relation to the crown's mechanical efficiency torque-WOB signature. A first range of mechanical efficiency is defined by a first weight on the bit (WOB) range from zero WOB to a threshold WOB, where the threshold WOB corresponds to a given WOB required just to penetrate the rock, further corresponding to a zero ( or negligible) depth of cut. The first range of mechanical efficiency further corresponds to a drilling efficiency of effective grinding. Another range of mechanical efficiency is defined by a different weight on the bit area from the threshold WOB to the optimal WOB, where the optimal WOB corresponds to a given WOB necessary to achieve only a maximum depth of cut with the bit, before the bit body enters contact with the soil formation. The second range of mechanical efficiency further corresponds to a drilling efficiency of effective cutting. A third range of mechanical efficiency is defined by the third bit weight range from the optimum WOB to an abrasive WOB, when the abrasive WOB corresponds to a given WOB necessary to cause the cutting torque of the bit to be substantially reduced zero, or becomes insignificant. The third area of mechanical efficiency is defined by the fourth weight on the crown area from the grinding WOB and above. The fourth range of mechanical efficiency further corresponds to a drilling efficiency of ineffective grinding. With regard to areas three and four, when the bit is at maximum cutting depth, while the WOB is further increased, frictional contact of the bit body with the rock formation is also increased.

Furthermore, mechanical efficiency model 152 uses a measure of drill bit wear from a previous iteration as input, which will be described further below in connection with the bit wear model.

With respect to bit wear model 156, in prediction mode, the bit wear model receives input from the lithology model via output 162, the rock strength model via output 166, and the mechanical efficiency model via output 170.1 In addition, the bit wear model 156 further receives 3-D bit model data at input 172. 3-D bit model input includes a drill bit work class and torque WOB signature. In response to the inputs of lithology, porosity, mechanical efficiency, rock strength, and 3-D bit model, the bit wear model 156 produces a measure of specific energy, total work, formation abrasiveness, and bit wear relative to the bit in the given formation, per unit depth, at the output 174. The specific energy is the total energy supplied to the bit, which is equal to the bit force divided by the cross-sectional area of the bit. Furthermore, the calculation of specific energy is based on the user-specified operating parameters. The overall work performed by the drill bit reflects both the rock strength and the mechanical efficiency. The calculation of total work performed by the drill bit is also based on the user-specified operating parameters. The formation's abrasiveness measure modulates an accelerated wear due to the formation's abrasiveness. Finally, the measure of bit wear corresponds to a state of wear associated with the bit's axial contact area and mechanical efficiency. As with calculations of specific energy and total work, the crown wear calculations are based on the user-specified operating parameters. In addition to output 174, the bit wear model 156 further includes provision of a measure of bit wear from a previous iteration to mechanical efficiency model 152 on output 176, where mechanical efficiency model 152 further uses the drill bit wear measure from a previous iteration in the calculation of its mechanical efficiency output data, on output 170 .

Reference is now made to the penetration rate model 158. The penetration rate model 158 receives mechanical efficiency and predicted torque via output 170 of mechanical efficiency model 152. Model 158 further receives bit wear via output 174 of bit wear model 156, rock strength via output 166 of rock strength model 148, and predicted HCE via output 184 of HCE model 154.1 addition, penetration rate model 158 further receives user-specified operating parameters, at input 186. In particular, the user-specified operating parameters include a user-specified weight on crown (WOB) and a user-specified RPM. As mentioned above, this predictive mode of operation is used to evaluate "what if" scenarios. In response to the inputs, the penetration rate model 158 produces a power level analysis and, in addition, a measure of penetration rate and economy of the drill bit and drilling system in the predicted drilling of a wellbore (or interval) in the formation, per unit depth, on output 188. More specifically, includes the power level analysis a determination of the maximum power level limit. The maximum power limit corresponds to a prescribed power which, when applied to the drill bit, maximizes the rate of penetration without causing shock damage to the bit. The operating power level resulting from the user-specified operating parameters may be less than or greater than the maximum power limit. Operating power levels that exceed the maximum power limit for the drill bit can be flagged automatically, e.g. by appropriate programming, to indicate or identify such intervals of a wellbore where shock damage to the drill bit is likely to occur. The power level analysis would apply to the particular drilling system, and its use in the drilling of a wellbore (or interval) in the given formation. In addition, the penetration rate is the predicted penetration rate at user-specified WOB and user-specified RPM. Finally, the economics include industry standard cost per foot analysis.

Calibration mode

Finally, in calibration mode, the goal or intent is to calibrate the drilling mechanics models to measured operating parameters. In addition, the geology models can be calibrated to measure core data. Furthermore, it is possible to partially or completely calibrate any model or group of models. Likewise, as with prediction mode, the operational limitations do not apply in calibration mode.

To begin with the geology models 142, measured core data can be used to calibrate each geology model. With respect to the lithology model, the lithology model 146 receives data from porosity logs, lithology logs, and/or mud logs, and in core data at input 160. As noted above, the porosity or lithology logs may include nuclear magnetic resonance (NMR), photoelectric, neutron density, sonic, gamma ray, and spectral gamma ray, or any other log sensitive to porosity or lithology. The mud logs are used to identify non-shale lithology components. Core data includes measured core data that can be used to calibrate the lithology model. Calibration of the lithology model with measured core data allows the predicted lithology composition to be in better agreement with measured core composition. Measured core porosity can also be used to calibrate any log-derived porosity. In response to the inputs, the lithology model 146 will provide a measure of lithology and porosity of the given formation per unit depth, at output 162. With respect to calibrated lithology, the output 162 preferably comprises a volume fraction of each desired lithologic component of the formation per unit depth, calibrated to a core analysis and/or sludge log. With respect to calibrated porosity, the log derived output 162 is preferably calibrated to measured core porosity. Also, less accurate logs can be calibrated to more accurate logs. The calibration of lithology and porosity on the output 162 is fed into the rock strength model 148, shale plasticity model 150, mechanical efficiency model 152, hole cleaning efficiency model 154, bit wear model 162, and penetration rate model 158.

With respect to the rock strength model 148, the inputs and outputs are similar to those discussed above in terms of the optimization mode. In calibration mode, however, input 164 further comprises core data. Core data includes measured core data that can be used to calibrate the rock strength model. The calibration allows the predicted rock strength to improve in accordance with the measured core strength. In addition, measured borehole pressure data can also be used to calibrate the confining stress calculation.

With respect to shale plasticity model 150, inputs and outputs are similar to those discussed above in terms of optimization mode. In calibration mode, however, the input 178 further comprises core data. Core data includes measured core data that can be used to calibrate the shale plasticity model. The calibration allows the predicted plasticity to be in better agreement with the measured core plasticity. In response to the inputs, the shale plasticity model 150 produces a measure of shale plasticity of a given formation per unit depth, at the output 180. With respect to calibrated shale plasticity, the output 180 preferably comprises a weighted average of the normalized clay properties that reflect the total plasticity calibrated to a core analysis.

With respect to mechanical efficiency model 152, inputs and outputs are similar to those discussed above in connection with the optimization mode, with the following exceptions. In calibration mode, input 168 does not include operating constraints or torque and drag analysis, while in calibration mode, however, input 168 includes measured operating parameters. Measured operating parameters include weight on crown (WOB), RPM, penetration rate, and torque (optional), which can be used to calibrate the mechanical efficiency model. In response to the inputs, mechanical efficiency model 152 will produce measures of total torque, bearing torque, friction torque, and calibrated mechanical efficiency, at output 170. With respect to total torque, total torque refers to total torque applied to the bit, which is further calibrated to measured torque if data is available. Cutting torque refers to the cutting component of total torque on the drill bit, which is further calibrated to a real mechanical efficiency. Friction torque refers to the friction component of the total torque on the crown, which is further calibrated to the actual mechanical efficiency. With regard to calibrated mechanical efficiency, mechanical efficiency is defined as the percentage of the total torque that cuts. The predicted mechanical efficiency is calibrated to the real mechanical efficiency. The calibration is more accurate if measured torque data is available. However, it is possible to partially calibrate mechanical efficiency if torque data is unavailable, using a predicted torque along with other measured operating parameters.

In calibration mode, an analysis of mechanical efficiency by range, i.e. by ranges of mechanical efficiency with respect to a bit's mechanical efficiency torque (WOB) signature, can also be included. As indicated above, the first range of mechanical efficiency is defined by the first weight on the bit (WOB) range from zero WOB to a threshold WOB, where the threshold WOB corresponds to a given WOB required to just penetrate the rock, further corresponding to a zero (or negligible) depth of cut. The first range of mechanical efficiency further corresponds to a drilling efficiency of effective grinding. The second range of mechanical efficiency is defined by the second weight on the bit area four threshold WOB to an optimal WOB, where the optimal WOB corresponds to a given WOB necessary to achieve only a maximum depth of terrain with the bit, before the body of the bit comes into contact with the soil formation. The second range of mechanical efficiency further corresponds to a drilling efficiency of effective cutting. The third range of mechanical efficiency is defined by a third weight on the bit range from the optimum WOB to an abrasive WOB, where the abrasive WOB corresponds to a given WOB necessary to cause the cutting torque of the drill bit to be reduced to the substantially zero, or to become insignificant. The third range of mechanical efficiency further corresponds to a drilling efficiency of ineffective cutting. Finally, the fourth range of mechanical efficiency is defined by a fourth weight on crown range from the abrasive WOB and above. The fourth range of mechanical efficiency further corresponds to a drilling efficiency of ineffective grinding. With regard to areas 3 and 4, while the bit is at a maximum cutting depth, while the WOB is further increased, frictional contact of the bit body with the rock formation is also increased.

With respect to bit wear model 156, inputs and outputs are similar to those discussed above with respect to optimization mode. In calibration mode, however, input 172 includes a bit wear measurement. The drill bit wear measurement includes a measure of a continuous axial contact area with the bit. Furthermore, the bit wear measurement is correlated with the total work done by the bit based on the measured operating parameter. In response to the inputs, the bit wear model 156 becomes a measure of specific energy, total work, calibrated formation abrasiveness, and caliber bit work class with respect to a given drilling system and formation, per unit depth, at output 174. With respect to specific energy, specific energy corresponds the total energy supplied by the drill bit. In addition, specific energy is equivalent to the drill bit force divided by the cross-sectional area of the drill bit, where the calculation is further based on the measured operational parameters. With regard to total work, the total work performed by the bit will reflect both the rock strength and mechanical efficiency. In addition, the calculation of total work is based on the measured operational parameters. With regard to calculated formation abrasiveness, the bit wear model will accelerate wear due to formation abrasiveness. Furthermore, bit wear measurements and total work done can be used to calibrate the formation's abrasiveness. Finally, with regard to calibrated drill bit work class, the wear condition of the dull drill bit is associated with total work performed. In calibration mode, the drill bit's work class for a given drill bit can be calibrated to the drill bit's wear measurement and the overall work performed.

With respect to hole cleaning efficiency model 154, the inputs and outputs are similar to those discussed above in connection with the optimization mode. In calibration mode, however, the hole cleaning efficiency is calibrated by correlating the measured HCE in the penetration rate model, further discussed below. With respect to the penetration rate model 158, the inputs and outputs are similar to those discussed above in connection with the optimization mode. In calibration mode, however, input 186 does not include operational constraints, but instead, input 168 includes measured operational parameters and bit wear measurement. Measured operating parameters include weight on crown (WOB), RPM, penetration rate, and torque (optional). Bit wear measurements are a measure of continuous axial contact area of the bit, and also identify the dominant type of wear, including uniform and uneven wear. For example, impact damage is a form of uneven wear. Measured operating parameters and bit wear measurements can be used to calibrate the penetration rate model. In response to the inputs, the penetration rate model 158 will produce a measure of calibrated penetration rate, calibrated HCE, and calibrated power limit. With respect to calibrated penetration rate, calibrated penetration rate is a predicted penetration rate given the measured operating parameters. The predicted penetration rate is calibrated to the measured penetration rate using HCE as a correction factor. With respect to calibrated HCE, HCE is defined as the actual over predicted penetration rate. The predicted HCE from the HCE model is calibrated to the HCE calculated in the penetration rate model. Finally, with respect to the calibrated power limit, the maximum power limit will maximize the penetration rate without causing shock damage to the bit. If the operational power level resulting from the measured operational parameters exceeds the power limit, impact damage is likely. Software or computer program to implement the prediction of the performance of the drilling system can be set up to automatically flag any operating power level that exceeds the power limit. Furthermore, the power limit can be adjusted to reflect the type of wear actually seen on the blunt drill bit. For example, if the program flags intervals where impact damage is likely, but the wear seen on the blunt bit is mostly uniform, the power limit is probably too conservative and should be raised.

A performance analysis can also be performed, which includes an analysis of operational parameters. Operating parameters to be measured include WOB, TOB (optional), RPM and ROP. Measurements close to the drill bit are preferred for more accurate performance analysis results. Other performance analysis measurements include bit wear measurements, drilling fluid type and hydraulics, and economics.

Overview

Reference is again made to figure 1. The apparatus 50 for predicting the performance of a drilling system for drilling a wellbore 14 in a given formation 24 will now be discussed further. The prediction apparatus 50 comprises a computer/controller 52 for generating a geological characteristic of the formation per unit depth according to a prescribed geological model, and for outputting signals representing the geological characteristic. The geological characteristics preferably include at least rock strength. In addition, the geology characteristic generation device 52 may further generate at least one of the following additional characteristics selected from the group consisting of log data, lithology, porosity, and shale plasticity.

The input device or devices 58 are arranged to introduce specifications of proposed drilling equipment for use in drilling the wellbore, where the specifications include at least one drill bit specification for a recommended drill bit. In addition, the input devices 58 can further be used to introduce additional proposed drilling equipment input specifications which may also include at least one additional specification of proposed drilling equipment, selected from the group consisting of a borehole motor, top drive motor, rotary drilling motor, mud system, and mud pumps.

Finally, the computer/controller 52 is further for determining a predicted drilling mechanics in response to specifications of the proposed drilling equipment as a function of the geology characteristic per unit depth according to a prescribed drilling mechanics model. The computer/controller 52 is further for outputting signals representing the predicted drilling mechanics, wherein the predicted drilling mechanics include at least one of the following, selected from the group consisting of bit wear, mechanical efficiency, power, and operating parameters. The operating parameters may include at least one of the following selected from the group consisting of crown weight, rotating RPM (revolutions per minute), cost, penetration rate, and torque. In addition, the rate of penetration includes instantaneous rate of penetration (ROP) and average rate of penetration (ROP-AVG).

As illustrated in Figure 1, the display 60 and the driver 62 each provide means responsive to the geological characteristics output and the predicted drilling mechanics output to generate a display of the geological characteristics and predicted drilling mechanics per unit depth. With respect to the printer 62, the geology characteristics and predicted drilling mechanics per unit depth comprise a printout 64. In addition, the computer/controller 52 may further generate drilling operation control signals on line 66, regarding given predicted drilling mechanics output signals. In such a case, the drilling system could further comprise one or more devices that are responsive to a drilling operation control signal based on a predicted drilling mechanism output signal to control a parameter in a current drilling of the wellbore with the drilling system. Examples of parameters may include at least one selected from the group consisting of crown weight, rpm, pump flow, and hydraulics.

Display of predicted performance

Reference is now made to figure 4. A display 200 of predicted performance of the drilling system 50 (figure 1) for a given formation 24 (figure 1) shall be described in more detail below. Display 200 comprises a display of geological characteristics 202 and a display of predicted drilling mechanism 204. The display of geological characteristics 202 comprises at least one graphic presentation selected from the group consisting of a curve representation, a percentage graph representation, and a band representation. In addition, the display of the predicted drilling mechanism 204 includes at least one graphical representation selected from the group consisting of a curve representation, a percentage graph representation, and a band representation. In a preferred embodiment, the at least one graphical representation of the geological characteristic 202 and the at least one graphical representation of the predicted drilling mechanism 204 are color coded.

Description

The following is a list of the various symbols, corresponding brief descriptions, units, and data ranges associated with the various columns of information illustrated in Figure 4. Note that this list is by way of example only, and is not intended to be limiting. It is included here to provide a thorough understanding of the illustrations in Figure 4. Other symbols, descriptions, units and data ranges are possible.

Depth, log data, lithology. porosity

As shown in Figure 4, the depth of the formation 206 is expressed in terms of a numerical representation. Log data 208 is expressed in the form of a curve representation, where log data 208 includes any log type sensitive to lithology and porosity. Lithology 210 is expressed in the form of a percentage graph for use in identifying different types of rock in a given formation, where the percentage graph illustrates a percentage of each type of rock at a given depth as determined from any log type sensitive to lithology. In one embodiment, the lithology percentage graph is color coded. Porosity 212 is expressed in the form of a curve representation, where the porosity is determined from any log type that is sensitive to porosity.

Rock strength

On display 200 in Figure 4, rock strength 214 is expressed in the form of at least one of the following representations, selected from the group consisting of a curve representation 216, a percentage graph representation (not illustrated, but similar to 210), and a band representation 218. The curve representation 216 of rock strength comprises limited rock strength 220 and unconfined rock strength 222. An area 224 between the respective curves of limited rock strength 220 and unconfined rock strength 222 is graphically illustrated, and represents an increase in rock strength as a result of a confining stress. the band representation 218 of rock strength provides a graphical illustration indicating a discrete range of rock strength at a given depth, and more generally, different discrete ranges of rock strength along a given wellbore. In a preferred embodiment, the band representation 218 of rock strength is color coded, comprising a first color representing a low rock strength range, a second color representing a hard rock strength range, and additional colors representing one or more intermediate rock strength ranges. Furthermore, the color blue can be used to indicate the low rock strength range, red to indicate a hard rock strength range, and yellow to indicate an intermediate rock strength range. A legend 226 is shown on the display to aid in the interpretation of the various display geology characteristics and predicted drilling mechanics.

Shale plasticity

On display 200 of Figure 4, shale plasticity 228 is expressed in terms of at least one of the following representations, selected from the group consisting of a curve representation 230, a percentage graph representation (not illustrated but similar to 210), and a band representation 232. The curve representation 230 of shale plasticity 228 comprises at least two curves of shale plasticity parameters selected from the group consisting of water content, clay type and clay volume, further wherein the shale plasticity is determined from the water content, clay type and clay volume according to a prescribed shale plasticity model 150 (Figure 3). In addition, the representations for shale plasticity are preferably color-coded. The band representation 232 of shale plasticity 228 provides a graphical illustration indicating a discrete region of shale plasticity at a given depth, and more generally, to different discrete regions of shale plasticity along the given wellbore. In a preferred embodiment, the band representation 232 of shale plasticity 228 is color coded, comprising a first color representing a region of low shale plasticity, a second color representing a region of high shale plasticity, and other colors representing one or more intermediate regions of shale plasticity. Furthermore, the color blue can be used to indicate the area of low shale plasticity, red can be used to indicate high shale plasticity, and yellow can indicate an intermediate area of plasticity. As noted above, the legend 226 on the display 200 will aid in an interpretation of the various display geological characteristics and predicted drilling mechanics.

Drill bit work / wear conditions

Bit wear 234 is determined as a function of total work done according to a prescribed bit wear model 156 (Figure 3). On display 200 in Figure 4, drill bit wear 234 is expressed in the form of at least one of the following representations, selected from the group consisting of a curve representation 236 and a percentage graph representation 238. The curve representation 236 of drill bit wear can include drill bit work expressed as specific energy level at the drill bit, total work performed of the drill bit, and optional work losses due to grinding. With respect to the percentage graph representation, bit wear 234 may be expressed as a graphically illustrated percentage graph 238 indicating a bit wear condition at a given depth. In a preferred embodiment, the graphically illustrated bit wear percentage graph 238 is color coded, comprising a first color 240 representing expired bit life, and a second color 242 representing remaining bit life. Furthermore, the first color is preferably red and the second color is preferably green.

Mechanical efficiency

Drill bit mechanical efficiency is determined as a function of bit torque/weight signature for a given drill bit according to a prescribed mechanical efficiency model 152 (Figure 3). On display 200 in Figure 4, drill bit mechanical efficiency 244 is expressed in the form of at least one of the following representations, selected from the group consisting of a curve representation 246 and a percentage graph representation 248. The curve representation 246 of drill bit mechanical efficiency includes total torque (TOB(ft- lb)), and cutting torque (TOB-CUT (ft-lb)) at the bit. The percentage graph representation 248 of bit mechanical efficiency 244 graphically illustrates total torque, where total torque includes cutting torque and friction torque components. In a preferred embodiment, the graphically illustrated percentage graph 248 of mechanical efficiency is color coded, comprising a first color to illustrate cutting torque 250, a second color to illustrate frictional unrestricted torque 252, and a third color to illustrate frictional limited torque 254. Legend 226 also provides help in interpreting the various torque components of mechanical efficiency. Furthermore, the first color is preferably blue, the second color is preferably yellow, and the third color is preferably red.

In addition to the curve representation 246 and percentage graph 248, mechanical efficiency 244 is further represented in the form of a percentage graph 256 which illustrates the operational limitations of the drilling system which have an adverse effect on mechanical efficiency. The operating constraints of the drilling system correspond to constraints that result in friction-limited torque occurring, (e.g., as illustrated by reference numeral 254 in the percentage graph 248), where the percentage graph 256 further indicates a corresponding percentage of impact that each constraint has on the friction-limited torque component of the mechanical efficiency at a given depth. Drilling system operating limitations may include maximum torque on the bit (TOB), maximum weight on the bit (WOB), minimum revolutions per minute (RPM), maximum rate of penetration (ROP), in any combination, and an unrestricted condition. In a preferred embodiment, the percentage graph representation 256 of the drilling system operating limitations on mechanical efficiency is color coded, comprising different colors to identify different limitations. The legend 226 is further provided to aid in an interpretation of the various drilling systems' operational limitations on mechanical efficiency in relation to the percentage graph representation 256.

Effect

On display 200 in Figure 4, power 258 is expressed in the form of at least one of the following representations, selected from the group consisting of curve representation 260 and a percentage graph representation 262. Curve representation 260 for power 258 comprises a power limit (POB-LIM(hp)) and operational power level (POB(hp)). The power limit (POB-LIM(hp)) corresponds to a maximum power that can be supplied to the drill bit. The operational power level (POB(hp)) comprises at least one of the following, selected from the group consisting of limited operational power level, recommended operational power level, and predicted operational power level. With respect to the curve representation 260, a difference between the power limit (POB-LIM(hp)) and operational power level (POB(hp)) curves is indicative of a limitation.

Effect 258 is further represented in the form of a percentage graph representation 262 which illustrates the operational limitations of the drilling system which have an adverse effect on the effect. The operational limitations of the drilling system correspond to the limitations that result in loss of power. Power limitation percentage graph 262 is further to indicate a corresponding percentage of impact that each limitation has on the power at a given depth. In a preferred embodiment, the percentage graph representation 262 of the drilling system's operational limitation on power is color coded, comprising different colors to identify different limitations. Furthermore, red is preferably used to identify maximum ROP, blue is preferably used to identify maximum RPM, and dark blue is preferably used to identify an unrestricted condition. The legend 226 further provides assistance in interpreting the various drilling systems' operational limitations on the effect with respect to the percentage graph representation 262.

Operating parameters

As shown in Figure 4, operating parameters 264 are expressed in the form of a curve representation 266. As discussed above, the operating parameters may include at least one of the following selected from the group consisting of crown weight, rotating RPM (revolutions per minute), cost, penetration rate , and torque. In addition, the penetration rate can include instantaneous penetration rate (ROP) and average penetration rate (ROP-AVG).

Drill bit selection/recommendation

Display 200 further provides a means for generating a display 268 of details of proposed or recommended drilling equipment. That is, details of the proposed or recommended drilling equipment are shown along with the geology characteristic 202 and predicted drilling mechanics 204 on display 200. The proposed or recommended drilling equipment preferably includes at least one bit selection used to predict the performance of the drilling system. In addition, first and second drill bit selections, indicated by reference numerals 270 and 272, are recommended for use in a predicted performance of drilling the wellbore. The first and second bit selections are identified by respective first and second identification numbers 276 and 278, respectively. The first and second identification numbers, 276 and 278 respectively, are also shown with geological characteristics 202 and predicted drilling mechanics 204, further where the positioning of the first and second identification numbers on the display 200 is selected to correspond to the areas of the predicted performance to which the first and second drill bit selections respectively apply. Further, the display may include an illustration of each recommended drill bit selection and corresponding drill bit specifications.

Broken line

Reference is still made to Figure 4. The display 200 further comprises a drill bit selection change indicator 280. The drill bit selection change indicator 280 is arranged to indicate that a change in the drill bit selection from a first recommended drill bit selection 280 to a second recommended drill bit selection 272 is necessary at a given depth. The bit selection change indicator 280 is preferably displayed on the display 200 along with the geology characteristics 202 and predicted drilling mechanics 204.

The method and apparatus according to the present description thus advantageously enable an optimization of a drilling system and its use in a drilling program to be achieved early in the drilling program. The present method and apparatus further facilitate the performance of appropriate improvements early in the drilling program. Economic benefits resulting from the improvements made early in the drilling program are advantageously multiplied by the number of wells that remain to be drilled in the drilling program. Important and significant savings for a company that commissions the drilling program can be advantageously achieved. Furthermore, the present method and apparatus enable the performance of measurements during drilling for each wellbore, all the way through a drilling program, for the purpose of verifying that the particular drilling system equipment is being used optimally. Furthermore, drilling system equipment performance can be more easily monitored with the method and apparatus of the present disclosure, in addition to identifying potential adverse conditions before they actually occur.

Furthermore, using the present method and apparatus, the time required to achieve a successful drilling operation in which a given oil-producing well of a number of wells is brought into line will be substantially reduced. The method and apparatus according to the present description thus produce an increased efficiency of the operation. Furthermore, the use of the present method and apparatus is particularly advantageous for a development project, e.g. to establish around 100 wells over a 3-year period in a given geographical area. With the present method and apparatus, a given well can be completed and brought on line, i.e. to marketable production, in about 30 days, for example, versus 60 days (or more) using previous methods. With the improved efficiency of the drilling performance of a drilling system according to the present disclosure, a gain in time to oil production is possible, which further translates into millions of dollars made available by an early date for marketing. Alternatively, for a given time period, using the present method and apparatus, one or more additional wells may be completed beyond the number of wells that would be completed using previous methods in the same time period. In other words, drilling a new well in a shorter time is advantageously converted into marketable production for an earlier date.

The present embodiments advantageously provide for an evaluation of various proposed drilling equipment before and during an actual drilling of a wellbore in a given formation, and further for use in connection with a drilling program. Drilling equipment, its selection and use, can be optimized for a specific interval or intervals of a wellbore (or interval) in a given formation. The drilling mechanics models take advantage of the effects of progressive bit wear under alternating lithology. Recommended operating parameters reflect the wear condition of the drill bit in the specific lithology, and also take into account the operating limitations of the particular drilling rig being used. A printout or display of the geological characteristics and predicted drilling mechanics per unit depth for a given formation provides key information that is very useful to a drilling operator, particularly for use in optimizing the drilling process for a drilling program. The printout or display also advantageously provides a clear display of expected drilling conditions and recommended operating parameters.

The present embodiments produce large volumes of complicated and critical information that are communicated clearly, e.g. in graphic format as illustrated and described here with reference to figure 4.1 addition, the use of color in the graphic format further accentuates key information. Furthermore, the display 200 advantageously produces a driller's road map. For example, with the display as a guide, the driller can be assisted with a decision about when to pull out a given drill bit. The display provides further information regarding the effects of operational limitations on performance and drilling mechanics. Furthermore, the display helps to select recommended operating parameters. With the use of the display, more efficient and safe drilling can be achieved. More beneficial, important information is clearly communicated.

Real-time aspects

According to another embodiment of the present disclosure, the apparatus 50 (Figure 1) is as discussed above, and further includes real-time aspects as discussed below. Specifically, computer controller 52 is responsive to a predicted drilling mechanics output signal to control a control parameter when drilling a wellbore with the drilling system. The control parameter includes one of the following parameters consisting of weight on the drill bit, rpm, pump flow rate, and hydraulics. In addition, the controller 52, logging instrumentation 16, measurement device processor 44, and other suitable devices are used to obtain at least one measurement parameter in real time during the drilling of the wellbore, as discussed herein.

The computer controller 52 further comprises a device for history matching of the measurement parameters with the back-calculated value of the measured parameter. In particular, the back-calculated value of the measurement parameters is a function of the drilling mechanics models and at least one control parameter. In response to a prescribed deviation between the measured parameter and the back-calculated value of the measured parameter, the controller 52 performs at least one of the following: a) adjusts the drilling mechanics model, b) modifies the control of a control parameter, or c) performs an alarm operation.

According to another embodiment of the present disclosure, the method and apparatus for predicting the performance of a drilling system includes a device for measuring a prescribed real-time drilling parameter during the drilling of a wellbore in a given formation. The borehole parameters can be obtained during the drilling of the wellbore using suitable commercially available measurement devices (such as MWD devices) to obtain the given real-time parameter. The drilling system apparatus further operates in a prescribed real-time mode to compare a given real-time drilling parameter with a corresponding predicted parameter. Accordingly, the present embodiment facilitates one or more modes of operation, either alone or in combination, in a one-time, repetitive or cyclic manner. The operating modes can e.g. include a prediction mode, a calibration mode, an optimization mode, and a real-time control mode.

In yet another embodiment of the present disclosure, the computer controller is programmed to perform real-time functions as described herein, using programming techniques known in the art. A computer-readable medium, such as a computer disk or other medium for communicating computer-readable code (a global computer network, satellite communications, etc.) is included, the computer-readable medium having a computer program stored thereon. The computer program for implementing a computer controller 52 is similar to that previously described, and has additional features for real-time capability.

With respect to real-time capability, the computer program includes instructions for controlling a control parameter during drilling of a wellbore with the drilling system in response to a predicted drilling mechanics output signal, wherein the control parameter includes at least one selected from the group consisting of bit weight, rpm, pump flow rate, and hydraulics. The computer program also includes instructions for obtaining a measurement parameter in real time while drilling the wellbore. Finally, the computer program comprises instructions for history fitting the measurement parameter with a back-calculated value of the measurement parameter, wherein the back-calculated value of the measurement parameter is a function of at least one of the following selected from the group consisting of the drilling mechanics model and at least one control parameter. The instruction to control the control parameter further includes instructions, in response to a prescribed deviation between the measured parameter and the back-calculated value of the measurement parameter, to perform at least one of the following: a) adjustment of the drilling mechanics model, b) modifying control of the control parameter, or

c) execution of an alarm operation.

In one embodiment of the drilling prediction analysis system, the system performs history matching by looking at the actual data collected during the drilling of a wellbore and comparing the actual data with predictions made during the corresponding planning phase. In response to the result of the history matching, some factors (eg, underlying assumptions) in the drilling mechanics prediction model may need to be adjusted to achieve a better fit of the predicted performance with the actual performance. These adjustments may be due to various factors related to the formation environment, which are unique to the particular geographic area, and how the environment fits with the particular bit design.

As noted, the real-time aspects of the present embodiment include performing comparisons of predicted performance with actual parameters while the wellbore is being drilled. With the real-time aspects, the present embodiment overcomes a disadvantage over a final analysis, i.e. with final analysis "lessons learned", can only be applied to subsequent wells. In contrast, with the real-time aspects of the present embodiment, any necessary adjustments to a drilling mechanics prediction model (applicable to the well being drilled) can be made, as well as making other appropriate adjustments to better optimize the drilling process on that particular well. The real-time aspects further accelerate the learning curve in relation to a well (or wells) in a given field, and the corresponding optimization process for each well. All these advantages are independent of the use of the drill bit as a measuring tool, as discussed further below.

Real-time optimization

Reference is now made to Figure 5, where there is shown a display 300 of the predicted performance of a drilling system for a given formation according to an embodiment of the present description, further in conjunction with the drilling prediction analysis and control system 50 of Figure 1, as previously described . Display 300 includes plots of data against depth, where the data includes depth 302, logging data 304, lithology 306, porosity 308, rock strength 310, bit wear 312, and operational parameters 314. Data shown for each respective plot is obtained as discussed earlier herein in connection with the figures 1 to 4, and as discussed below.

A first area 316 of the display 300 is characterized by information and data regarding respective depths above the depth location of MWD sensors. Such information in the first area 316 is generally considered accurate if the data was collected and analyzed after the job was completed. Accordingly, the data in the first area 316 appears to some extent as a "calibration mode" for an end job case. The solid line 318 within the operating parameter column 314 denotes an actual ROP, and the broken line 320 represents what the prediction model would have predicted for the ROP from the log calculated rock strength 310 using actual drilling parameters (eg, WOB 322 and RPM 324).

In an "end of job" mode, the drilling prediction analysis and control system compares the predicted against the actual ROP to test the accuracy of the prediction model on the given well and to make adjustments as necessary for subsequent wells in the particular field or area. For a real-time (RT) job, the predictive analysis and control system 50 (Figure 1) makes adjustments in the early drilling stages of a bit run in a given wellbore, until a close history fit is achieved, to indicate that the predictive model is working well in the given environment. Consequently, the drilling prediction analysis and control system is in a position to better predict future ROPs assuming good displacement information. The better predicted future ROP can help the drill prediction analysis and control system to determine when a drill bit will be dull and should be pulled out, in later wells in the particular field.

Drill bit as a measuring tool

While the following example concerns a backcalculation of rock strength, it is possible to make a backcalculation in connection with different parameters as described here. Reference is again made to Figure 5, where another area 326 is characterized by information and data corresponding to respective depths in the area between the drill bit and the MWD sensors. The drilling parameter data (eg WOB, RPM and ROP) is known at the drill bit depth, as it can be measured almost instantaneously. The drilling prediction analysis and control system 50 (Figure 1) achieves a good ROP history fit in the area 316 above the MWD sensors. Accordingly, the drilling prediction analysis and control system 50 is able to back-calculate some "inferred" measurement parameters from the actual drilling parameters, and a resulting ROP at a given depth or depths.

The "implied" parameters refer to a parameter (or parameters) occurring within the region 326 in the interval between the depth corresponding to the bit and the MWD sensors, and accordingly, the "implied" parameters cannot be calculated from measured data, since the measuring device has not yet crossed the interval during a given time period. After relevant MWD sensor data becomes available, the drilling prediction analysis and control system 50 can determine lithology and rock strength parameters from there. For example, drilling prediction and analysis and control system 50 can then compare an "indicated" rock strength with a log-calculated rock strength. In Figure 5, log calculated rock strengths are illustrated as a solid line 328, and the "implied" rock strength is illustrated as a dotted line 330.

The following discussion illustrates ways in which the drilling prediction analysis and control system 50 can make use of these above discussion techniques to determine an "indicative" parameter. If a measurement "at the crown" measurement began to deviate from a "verification" measurement, the drill prediction analysis and the control system could indicate that something has gone wrong in the borehole. The drill bit may have been damaged or packed up, the hole cleaning efficiency may be a problem, the drilling efficiency may have changed, etc. There may also be cases in which the drilling prediction analysis and control system 50 uses suggested parameter value for some other calculations, to a corresponding real measurement parameter value can be derived from log data, e.g., as available in area 316.

When good awiks data is available, the drilling prediction analysis and control system 50 can rely on this to help optimize the well being drilled. However, when an exploration well is drilled without awiks information, the drilling prediction analysis and control system will use the "implied data" from the drilled well to optimize this well.

In other words, the values of the back-calculated measurement parameters are adjusted to history or compared with values of the measurement parameters. In a first case, back-calculated measurement parameters correspond to values in a first interval of the wellbore above the level of the MWD sensors (such as the area 316 in Figure 5). With respect to backcalculated values in this first interval, the drill prediction analysis and the control system will perform a history match. One reason for this history adjustment in the first interval is for the drilling prediction analysis and the control system to determine whether the drilling mechanics model(s) are working correctly.

In the first interval, with respect to any deviation in the history fit comparison greater than a prescribed amount, the drilling analysis and control system will make appropriate adjustments to the drilling mechanics model used to generate the predicted drilling mechanics. Specifically, the drilling prediction analysis and control system adjusts the underlying assumptions for a respective model until an acceptable level of deviation is achieved (ie, until a history fit deviation between the measured parameters and the back-calculated value of the measured parameters is within an acceptable level of deviation).

Furthermore, in connection with the first interval, after making appropriate adjustments to one or more respective drilling mechanics models, drilling analysis and the control system will improve a corresponding prediction of the drilling mechanics for further drilling of the wellbore. In other words, drilling analysis and the control system fine-tune the drilling mechanics models during the drilling process. In response, the drilling system will change control of one or more control parameters, as appropriate, based on the fine-tuned drilling mechanics model. Fine tuning helps to optimize drilling parameters while drilling the well continues forward.

In another case, within a different interval of the wellbore between the MWD measuring devices and the drill bit (such as area 326 of Figure 5), the drilling prediction analysis and control system uses a history fit of a measurement parameter to back-calculate the value of the measurement parameter in a slightly different way from the first interval. One reason for the history adjustment in the second interval is so that drill prediction analysis and the control system will gain insight into the condition of the drill bit and how the drill bit interacts with the formation.

Within the second interval, if the history fit shows a deviation greater than a prescribed limit, the deviation in the history fit indicates a potential problem (eg, at the bit) in the drilling of the wellbore with the drilling system. Otherwise, a deviation in the history fit within an acceptable margin indicates drilling of the wellbore with the drilling system as predicted. When it concerns back-calculated values of the measurement parameters in the second interval, the back-calculated value is indicated by real parameters when drilling the wellbore (without geological values) for the respective interval.

The real-time features discussed here provide a powerful addition to drilling predictive analytics and control system capabilities.

Accordingly, the drilling system, method and apparatus of the present invention may operate in a prescribed manner to implement a prediction mode, followed by a drilling mode. A comparison of parameters obtained in the predicted mode and parameters obtained in the drilling mode can provide useful insight when it comes to modifying and/or making adjustments in connection with the prediction models and the drilling of a given well or a subsequent well. The drilling system method and apparatus also perform drilling optimization by examining real-time parameters with respect to predicted parameters (eg, a predicted rock strength) per unit depth, and making appropriate adjustments (eg, to the underlying assumptions used in the drilling mechanics models).

The drilling prediction device can be placed in a different location than the actual drilling site. That is, the prediction apparatus may be at a remote location that interfaces with the real drilling site via a global communication network, such as via the Internet or the like. The prediction apparatus may also be located at a real-time operations center (ROC), where the ROC has a satellite link or other suitable communication link to the drilling site and the drilling apparatus.

The present embodiment also facilitates the use of the prescribed drill bit as a measuring device while drilling a wellbore. With a formation change during the drilling of the wellbore, such as a change in the compressive strength of the rock, there is a corresponding change in the bit's response during the drilling of the wellbore. For example, with a change in formation, the bit may become unbalanced, vibrate or undergo other similar changes. The drilling system's apparatus monitors such changes in a bit's performance using appropriate measuring devices. For example, one way to monitor a bit's performance is via a suitable sensor at the bit.

The drilling system's apparatus may also include typical measurement while drilling (MWD) sensors located in the drill string behind the drill bit. For example, the MWD sensors are at a distance from the bit on the order of about 50 to 100 feet. As a result, measurements taken by the MWD sensors will lag behind the drill bit in real time while drilling the wellbore. Regarding drill bit wear parameters, the method according to the present embodiment comprises drilling a well hole, and during drilling, comparing a back-calculated drill bit wear parameter (as determined from MWD measurements) with the predicted drill bit parameter. The method further comprises a build-up of the bit wear condition in which measured bit wear is periodically updated in relation to the predicted wear, and suitable adjustments are recommended and/or performed to achieve an overall best drilling performance. In other words, the predicted wear performance can be compared to a real-time measured parameter representing a measured bit wear performance.

The present embodiments also facilitate a de facto same-day "real-time" optimization and calibration, compared to a subsequent optimization and calibration on the order of one or more weeks. Real-time optimization and calibration advantageously has a positive effect on the drilling performance of the drill bit during the drilling of a well hole. Accordingly, the drilling system and method of the present embodiments will facilitate appropriate parameter adjustments to better match the real world scenario based on the result of a comparison (or history fit) of actual versus predicted drilling parameters and performance.

When a difference in an actual parameter versus a predicted parameter is uncovered (ie, beyond a predetermined maximum amount), the drilling system method and apparatus of the present embodiment act in response thereto according to a prescribed response. For example, in response to an evaluation of a history fit deviation outside a given limit, the drilling system and method will adjust various parameters as a function of the outcome of the comparison of actual versus predicted drilling performance. The comparison of actual versus predicted drilling parameters can give an indication of unfortunate or unwanted bit wear. A further test can give an indication of whether the deviation is really due to bit wear or another unfortunate condition.

In an example scenario, the drilling system may operate between an automatic drill control mode and a manual control mode. In response to a difference in a history match outside a prescribed limit, the embodiment of the present invention may perform an alarm operation. An alarm operation may include producing an indication that something has gone wrong and that attention is required. The system and method may also be switched out of an automatic drilling control mode and placed in the manual control mode until such time that the corresponding discrepancy is resolved.

The drilling system apparatus and method may also perform an alarm operation that includes appropriate warning indicators, such as color-coded indicators or other suitable indicators appropriate for a given display and/or field application. In a given alarm operation, prescribed information contained in the display may be illuminated, animated, etc., in such a way as to draw attention to the corresponding information.

A red indicator can e.g. be arranged to represent that a potential for premature bit failure exists. Such premature bit failure can be imagined when a prescribed parameter versus an actual parameter differs by more than a prescribed maximum amount of difference. A yellow indicator can indicate a caution condition, where the prescribed parameter versus an actual parameter differs by more than a prescribed minimum differential amount, but less than the maximum differential amount. Finally, a green indicator may indicate a totally acceptable condition, where the prescribed parameter versus the actual parameter differs by less than a minimum differential amount. In the latter situation, the forecast is really on course, and drilling can continue relatively undisturbed.

The present invention thus produces a form of alarm or early warning. A real-time decision to adjust or not to adjust can then be given in a more informed way than previously possible. The present embodiment further provides a real-time observation for drilling a wellbore, e.g. by using the display.

In further discussion in connection with actual versus predicted performance of a drill bit in drilling a wellbore, it is noted that the drill bit is first in the borehole before the logging tool. Real-time parameters at the bit are ahead of the logging tool by a given amount. The advance state of the real-time parameters at the drill bit is expressed by time and distance, and such time and distance correspond to a time it takes the logging tool to cross a corresponding distance that the logging tool is separated from the drill bit along the drill string. With these real-time parameters, in conjunction with a suitable drilling mechanics model, certain measurements can be indicated such as a compressive strength of the rock being drilled by the drill bit. Other, for example, real-time parameters at the drill bit include WOB, RPM and torque.

With real-time parameters and measurement information, the drilling system apparatus uses instrumentation for logging while drilling (such as MWD equipment) to verify what the bit indicated, ie whether what was indicated was really there or not. The MWD logging tool can be used for continuous verification of what the bit is suggesting, as well as given the predicted parameters and the actual performance. For example, if the logging tool senses parameters that are proportional to rock strength, the parameter information is sent to the drilling system's prediction and analysis apparatus for processing. The prediction and analysis apparatus processes the pressure information to produce an indication of the true state of the rock being drilled. If the true state of the rock is as predicted, the drilling process can be allowed to continue. If not, the drilling process can be changed or modified as needed. Accordingly, the drilling prediction and analysis system can control the drilling of the wellbore in a prescribed manner. A prescribed way could include switching between an automatic drill control mode and a manual drill control mode.

Another example MWD tool includes a drill bit vibration measuring tool. Based on vibration data, the drill prediction and analysis system makes a determination as to whether a given drill bit is susceptible to downhole damage. An inflection point that may occur in the vibration measurement tool's output data indicates that a calibration or update of the vibration level may be necessary. Using a bit parameter optimization based on vibration data, the drill prediction and analysis system determines how much force a given bit can withstand without suffering significant or catastrophic damage. Such analysis may include the use of performance data derived from previous drill bit vibration/performance studies. As discussed herein, the drilling prediction and analysis system includes at least one computer-readable medium having appropriate programming code to perform the functions discussed herein.

The present invention also relates to an investigation of borehole stability problems. Using appropriate characterizations, borehole mapping can be performed to investigate fractures in a given formation. The orientation of cracks in the formation can have an effect on drillability. Mapping of fractures or cracks can give an indication of the extent to which the stone is damaged. A fracture is an indication of the presence of a rapid drop in rock strength.

It is also important to think about error minimization. There are many unknowns. Assigning the fault to a cause may be incorrect, if there is no direct quantification. This concerns assumptions against measurement. By using appropriate measurement downhole equipment, various log data can be routed to the surface. However, there may be many measurements down the borehole, where only selected ones are able to be sent to the surface. Such a limitation is mostly due to an inability of current technology to transmit all possible measurements to the surface simultaneously.

The drilling system's apparatus and method according to the present embodiment also make use of the drill bit as a measuring tool. For example, a vibration harmonic of the drill bit enables the use of the drill bit as a measuring tool. Vibration data can prove useful for calibration purposes. In an example of drilling a wellbore, the drill bit can be specified, taking into account available data regarding the particular lithology and to specify different parameters of WOB, torque and ROP.

The procedure includes drilling the well and monitoring the ROP, observing the lithology, and determining the WOB as part of the process. In this example, the bit is the first measuring device to start predicting what is being drilled, and the various logging tools verify the bit's measurements.

The present method and system's apparatus further comprises back-calculation of parameters, superimposition of the back-calculated parameters with the predicted parameters, and assessment and what actually happens. The procedure and the system apparatus will then fine-tune and/or make appropriate adjustments in response to the determination of what happens at the drill bit. Consequently, with the drill bit as a measuring tool, it is possible to have an advance warning of 50 to 100 feet to judge what is happening in the borehole at the drill bit.

In addition, using the drill bit as a measuring tool, one can judge whether the drill bit is still alive (ie able to continue drilling) or other appropriate judgments. For example, the bit measurement may indicate that the bit did something unexpected. An MWD sensor on the drill string can verify what the bit measurement indicated. Was the MWD sensor earlier or later than expected?. What is the appropriate action to take? Is it a mistake? Using a drill bit as a sensor, the prediction and analysis system is able to observe and/or measure vibration to indicate whether the drill bit is performing as predicted. Accordingly, the prediction and analysis system can update recommended drilling parameters based on what is observed when using the drill bit as a measuring tool. To look ahead (e.g. one foot in front of the drill bit), the prediction and analysis apparatus can adjust parameters to where the drilling apparatus is expected to be, in connection with the use of the drill bit as a measuring tool.

Using the drill bit as a measuring tool, the prediction and analysis system can test an anisotropy of the rock, directional characteristics, compressive strength, and/or porosity. For a horizontal well, there is a need for the drill bit to go 90° from vertical. If the relative dip angle changes, the porosity may still be the same.

In a history matching mode or optimization mode, the MWD sensor or sensors can be 50 to 100 feet behind the bit, at the bit, or measuring in front of the bit. In an operational mode, the system generates a proposal and uses the proposal during drilling of a wellbore. For example, the proposal may include a lithology and a predicted rock strength per unit depth. During drilling, the system will backcalculate the rock strength at a given depth, and then compare the backcalculated measure of rock strength to information available in response to the measurement tool crossing a corresponding boundary (ie passing the formation). The system then performs a history match of predicted rock strength and actual rock strength. After the history fitting, the system makes an appropriate parameter adjustment or adjustments.

The system performs history matching to verify or determine that the drilling system is responding as it was predicted to respond at the bit. The system also operates in a real-time mode that uses display mechanics and back-calculations of effective rock strength (predicted). As a sensor traverses at a given depth, the system calculates a compressive rock strength (or porosity) parameter. A mud logger can be used in connection with a measured rock strength against a predicted rock strength calibration, where the mud logger is suitably calibrated before use.

As discussed here, the drill prediction analyzes and the control system use data that is closer to the drill bit. Accordingly, the system and method will make other prior uncertainties much smaller. With regard to drilling a well hole, this is an improvement. Based on experience, it is common for an unexpected geology scenario to occur in deviation wells.

According to the present embodiments, real time can be characterized by a collapse of the time between when data is collected downhole and when the data is available to the drilling operator at a given time. That is, how long will it be before the drill operator for the data (two weeks versus one day). With the real-time aspect according to the drill prediction and analysis and control system, the system is able to determine what the drill bit is doing within a short period of time, and determine what needs to be adjusted, and output a revised WOB, RPM, or other appropriate operating parameters in real time.

With respect to bit wear, the drill analysis and control system includes a bit wear indicator. The drill bit wear indicator is characterized by the fact that while the drill bit wears, a signature or acoustic signal is generated which is different for different states of drill bit wear. This system also includes, via suitable measuring devices, an ability to measure the signature or the acoustic signal to determine a measurement of the wear condition of the drill bit.

As discussed herein, the operating parameters include at least one predicted RPM, WOB, COST, ROP, and ROP avg. These predicted operating parameters are shown on the display output of the drilling prediction analysis and control system 50 in Figure 1. Measurement parameters can include any parameter associated with the drilling of a wellbore that can be measured or found (such as by suitable calculations) in true time. A measurement parameter can comprise one or more operational parameters. Control parameters may include any parameter that may be subject to modification or control, either manually or via automatic control, to affect or alter the drilling of a wellbore. For example, control parameters may include one or more operating parameters that are subject to direct (or indirect) control.

Although only a few exemplary embodiments of this invention have been described in detail above, those skilled in the art will readily understand that many modifications are possible in the exemplary embodiments without significant deviations from the new information and advantages of the invention. Accordingly, all such modifications are intended to be included within the scope of the invention as defined in the following claims. In the claims, device plus function clauses are intended to cover the structures described herein to perform the stated function, and not only structural equivalents, but also equivalent structures.

Claims (50)

1. Device (50) for predicting the performance of a drilling system (10) for drilling a wellbore (14) in a given formation (24), the device comprising a computer control unit (52) for generating a geological characteristic (142) of the formation per unit depth according to a prescribed geological model (142) and outputting signals representing the geological characteristic (166), characterized in that the geological characteristic comprises at least rock strength, an input unit (58) for inputting specifications (270) of proposed drilling equipment for use in the drilling of the wellbore (14), wherein the specifications (270) comprise at least one drill bit specification of a recommended drill bit (276), a computer control unit (52) for determining predicted drilling mechanical parameters (144) in response to the specifications of the proposed drilling equipment that a function of the geology characteristic per unit depth according to a drilling mechanics model (144), and outputting signals representing the predicted drilling mechanics, where the prior soft drilling mechanics (144) comprises at least one of the following selected from the group consisting of drill bit wear (156), mechanical efficiency (152), power (258), and operating parameters (264), a computer control unit (52) responsive to an output signal representing predicted drilling mechanical parameters (52) for controlling a drilling parameter when drilling a wellbore (14) with the drilling system (10), wherein the control parameter comprises at least one selected from the group consisting of bit weight, RPM, pump flow rate, and hydraulics , measurement-while-drilling equipment for recording a measurement parameter in real time (16) during drilling of the wellbore (14), and a computer control unit (52) for history matching (114) of the measurement parameters with a back-calculated value of the measurement parameter, where back-calculated value of the measurement parameter is a function of the drilling mechanics model (144), and at least one control parameter, and where in response to a prescribed deviation between the measurement parameter and the back-calculated value of measurement parameter, said computer control unit performs at least one of the following selected from the group consisting of a) adjusting the drilling mechanics model, b) modifying or controlling the drilling parameter, and c) performing an alarm operation. 2. Device according to claim 1, characterized in that it further comprises a device that responds to the geology characteristic output signal and the predicted drilling mechanics output signal to generate a display (200) of the geology characteristic and predicted drilling mechanics per unit depth. 3. Device according to claim 2, characterized in that said display generation device (200) comprises at least one of the following, selected from the group consisting of a) a display monitor and b) a printer, where display of the geological characteristics and predicted drilling mechanics per depth unit comprises a printout. 4. Device according to claim 1, characterized in that the aforementioned geological character-strip generation device (142) further generates at least one of the following additional characteristics selected from the group consisting of log data, lithology, porosity, and shale plasticity. 5. Device according to claim 1, characterized in that the proposed drilling equipment input specification device (270) further comprises the submission of at least one further specification of proposed drilling equipment (276), selected from the group consisting of borehole motor, top drive motor, rotary drilling motor, mud system, and mud pump. 6. Device according to claim 1, characterized in that the operating parameters (264) comprise at least one of the following, selected from the group consisting of weight of the crown (120), rotating RPM (revolutions per minute), cost, penetration rate (188), and torque (170). 7. Device according to claim 6, characterized in that the penetration rate (188) comprises instantaneous penetration rate (ROP) and penetration rate (ROP-avg). 8. Device according to claim 2, characterized in that the display (200) of the geological characteristic comprises at least one graphical representation selected from the group consisting of a curve representation, a percentage graph representation, and a band representation, and in that the display of the predicted drilling mechanics comprises at least one graphical representation selected from the group consisting of curve representation, a percentage graph representation, and a band representation. 9. Device according to claim 8, characterized in that the said display generation device (200) comprises at least one of the following selected from a group consisting of a) a display monitor and b) a printer, where the display of the geological characteristics and the predicted drilling mechanics per depth unit comprises a printout. 10. Device according to claim 8, characterized in that at least one graphic representation of the geological characteristic (202) and the at least one graphic representation of predicted drilling mechanics are color coded. 11. Device according to claim 8, characterized in that the rock strength (214) is expressed in the form of at least one of the following representations selected from the group consisting of a curve representation, a percentage graph representation, and a band representation, where the curve representation of the rock strength (214) includes limited rock strength and unconfined rock strength, further wherein the area between respective curves of limited rock strength and unconfined rock strength is graphically illustrated and represents an increase in rock strength as a result of a confining stress, and the band representation of rock strength (214) provides a graphical illustration indicating a discrete range of rock strength at a given depth, further where the band representation of the rock strength is coded, comprising a first code representing a low area of rock strength, a second code representing an area of high rock strength, and further codes representing one or more intermediate areas of rock strength. 12. Device according to claim 8, characterized in that the mentioned geology characteristic generation device further generates at least one of the following additional characteristics selected from the group (202) consisting of logging data, lithology, porosity and shale plasticity, and where the operational parameters (264) comprise at least one of the following, selected from the group consisting of bit weight, bit RPM (revolutions per minute), cost, penetration rate, and torque. 13. Device according to claim 12, characterized in that log data is expressed in the form of a curve representation, where the log data (208) includes any log type that is sensitive to lithology and porosity, and where lithology (210) is expressed in the form of a percentage graph for use in identifying different types of rock within a given formation, where the percentage graph illustrates a percentage of each type of rock at a given depth, and porosity (212) is expressed as a curve representation, and shale plasticity (230) is expressed as of at least one of the following representations, selected from the group consisting of a curve representation, a percentage graph representation, and a band representation, where the curve representation of shale plasticity comprises at least one curve of shale plasticity parameters selected from the group consisting of water content, clay type and clay volume, and further where shale plasticity is determined from the water content, clay type and clay volume according to a prescribed shale plasticity m odell, and wherein the band representation of shale plasticity provides a graphical illustration indicating a discrete area of shale plasticity at a given depth, further wherein the band representation of shale plasticity is coded, comprising a code representing an area of low plasticity, another code representing an area of high plasticity, and additional codes representing one or more areas of intermediate shale plasticity. 14. Device according to claim 8, characterized in that drill bit wear (234) is determined as a function of cumulative work performed according to a prescribed drill bit wear model (156) and expressed in the form of at least one of the following representations selected from the group consisting of a curve representation and a percentage graph representation, where the curve representation of the bit wear may include bit work expressed as a specific energy level at the bit, cumulative work done by the bit, and optional work loss due to grinding, and the percentage graph representation indicates a bit wear condition at a given depth, further where the bit bit percentage graph is coded , comprising a first code representing expired bit life, and a second code representing remaining bit life. 15. Device according to claim 8, characterized in that the drill bit's mechanical efficiency (244) is determined as a function of torque/weight on the bit signature for the given drill bit according to a prescribed mechanical efficiency model (168), and expressed in the form of at least one of the following representations selected from the group consisting of a curve representation and a percentage representation, where the curve representation of the drill bit's mechanical efficiency (244) includes total torque and cutting torque at the drill bit, and the percentage graph representation of the drill bit's mechanical efficiency illustrates total torque, total torque including cutting torque and friction torque components, and further wherein the percentage graph representation of the bit's mechanical efficiency is coded, comprising a first code to illustrate cutting torque, a second code to illustrate friction-unlimited torque, and a third code to illustrate friction-limited torque. 16. Device according to claim 15, characterized in that mechanical efficiency (244) is further represented in the form of a percentage graph that illustrates the operational limitations of the drilling system which have an adverse effect on mechanical efficiency, where the operational limitations of the drilling system correspond to limitations which are a result of friction-limited torque, where the percentage graph further indicates a corresponding percentage of impact that each constraint has on friction-limited torque components of the mechanical efficiency at a given depth, where the drilling system operating constraints (168) may include maximum torque at the bit (TOB), maximum weight of the bit ( WOB), minimum and maximum bit revolutions per minute (RPM), maximum rate of penetration (ROP) in any combination, and unconstrained condition, further where the percentage graph representation of the drilling system operating limitations on mechanical efficiency is coded, comprising various codes for to identify different constraints. 17. Device according to claim 8, characterized in that power (258) is expressed in the form of at least one of the following representations selected from the group consisting of a curve representation and a percentage graph representation, where the curve representation for power includes power limits and operational power level, where the power limit corresponds to a maximum power supplied to the drill bit and the operational power level includes at least one of the following, selected from the group consisting of limited operational power level, recommended operational power level, and predicted operational power level, and the percentage graph representation of power illustrates drilling system operational limitations that have an adverse effect on the power, where the drilling system operational limitations correspond to those limitations which results in loss of power, where the power limitation percentage graph further indicates a corresponding percentage of impact that each limitation has on the power at a given depth, further where the percentage graph representation of the drilling system's operation s limitations on the effect are coded, comprising different codes to identify different limitations. 18. Device according to claim 2, characterized in that it comprises a device for generating a display (200) of details of proposed drilling equipment (268) together with geological characteristics (202) and predicted drilling mechanics (204), where the proposed drilling equipment comprises at least a recommended drill bit selection used to predict drilling system performance. 19. Device according to claim 18, characterized in that the first (270) and second (272) drill bit selections are recommended for use in a predicted performance of the drilling of the wellbore (14), and further where the first and second drill bit selections are identified with respective first (276) and second (278) identification numbers, where the first and second identification numbers are shown with geological characteristics (202) and predicted drilling mechanics (204), further where the placement of the first (276) and second (278) identification numbers on the display is chosen to correspond to areas of predicted performance to which the first (270) and second (272) drill bit selections apply. 20. Device according to claim 2, characterized in that it further comprises a drill bit selection change indicator (280) to indicate that a change in the drill bit selection from a first recommended drill bit selection (270) to a second recommended drill bit selection (272) is necessary at a given depth on the display of geological characteristics (202) and predicted drilling mechanics (204). 21. Method for predicting the performance of a drilling system (10) for drilling a well (14) in a given formation (24), wherein the method comprises generating a geological characteristic in the formation per unit depth according to a prescribed geological model (142), and to output signals representing the geological characteristic, characterized in that the geological characteristic comprises at least the rock strength, to obtain specifications (270) of proposed drilling equipment for use in drilling the well hole (14), where the specifications (270) comprise at least one drill bit specification of a recommended drill bit, determining a predicted drilling mechanics (204) in response to the specifications (270) of the proposed drilling equipment as a function of the geology characteristic (202) per unit depth according to a drilling mechanics model (144), and outputting signals representing the predicted drilling mechanics (204) , when the predicted drilling mechanics include at least one of the following selected from the group consisting of bit wear, mechanical vir power, power, and operating parameters, to control a control parameter (66) in drilling the wellbore with the drilling system in response to a predicted drilling mechanics output signal, wherein the control parameter comprises at least one selected from the group consisting of bit weight, RPM, pump flow rate, and hydraulics, obtaining a measurement parameter (106) in real time during the drilling of the wellbore, and history matching the measurement parameter (108) with a back-calculated value of the measurement parameter, wherein the back-calculated value of the measurement parameter is a function of at least one of the following, selected from the group consisting of of drilling mechanics model and at least one control parameter, and responsive to a prescribed deviation between the measurement parameter and the back-calculated value of the measurement parameter, wherein the further control step of performing at least one of the following selected from the group consisting of a) adjusting the drilling mechanics model, b) modifying the control of a control parameter, and c) to perform an alarm indication. 22. Method according to claim 21, characterized in that it further comprises generating a display (200) of the geological characteristic (202) and predicted drilling mechanics (204) per depth unit in response to the geological characteristic's output signal and the predicted drilling mechanics' output signal. 23. Method according to claim 22, characterized in that the generation of a display (200) comprises the use of at least one of the following, selected from the group consisting of a) a display monitor, and b) a printer, where the display of the geological characteristics and predicted drilling mechanics per depth unit includes a printout. 24. Method according to claim 21, characterized in that generation of the geology characteristic (202) comprises generation of at least one of the following additional characteristics selected from the group consisting of log data, lithology, porosity and shale plasticity. 25. Method according to claim 21, characterized in that generation of the proposed drilling equipment input specification (270) further comprises finding at least one further specification of proposed drilling equipment selected from the group consisting of borehole motor, top drive motor, rotary drilling motor, mud system, and mud pump. 26. Method according to claim 21, characterized in that the operating parameters (264) comprise at least one of the following, selected from the group consisting of weight of the drill bit, drill bit RPM (revolutions per minute), cost, penetration rate, and torque. 27. Method according to claim 26, further characterized in that the penetration rate (188) includes instantaneous penetration rate (ROP) and average penetration rate (ROP-avg). 28. Method according to claim 22, characterized in that displaying the geological characteristic (202) comprises displaying at least one graphic representation selected from the groups consisting of curve representation, percentage graph representation and a band representation, and displaying predicted drilling mechanics (204) comprises displaying at least a graphical representation selected from the group consisting of a curve representation, a percentage graph representation, and a band representation. 29. Method according to claim 28, characterized in that the generation of a display (200) comprises the use of at least one of the following, selected from the group consisting of a) a display monitor and b) a printer, where the display of the geological characteristic (202) and predicted drilling mechanics (204) per depth unit includes a printout. 30. Method according to claim 28, further characterized in that at least one graphical representation of the geological characteristic (202) and at least one graphical representation of predicted drilling mechanics (204) are color coded. 31. Method according to claim 28, characterized in that the rock strength (216) is represented in the form of at least one of the following representations, selected from the group consisting of a curve representation, a percentage graph representation, and a band representation, where the curve representation of rock strength (216) comprises limited rock strength and unconfined rock strength, and further wherein an area between respective curves of limited rock strength and unconfined rock strength is graphically illustrated and represents an increase in rock strength as a result of confining stress, and the band representation of rock strength (216) provides a graphical illustration indicating a discrete region of rock strength at a given depth, where further the band representation of rock strength is coded, comprising a first code representing an area of low rock strength, a second code representing an area of hard rock strength, and additional codes representing one or more areas of intermediate rock strength. 32. Method according to claim 28, characterized in that generation of the geological characteristic (202) further comprises the generation of at least one of the following additional character pieces, selected from the group consisting of logging data (208), lithology (210), porosity (212) and shale plasticity ( 228), and wherein the operating parameters (264) comprise at least one of the following, selected from the group consisting of bit weight, bit RPM (revolutions per minute), cost, penetration rate, and torque. 33. Method according to claim 32, characterized in that log data (208) is expressed in the form of a curve representation, where the log data includes any log type that is sensitive to lithology and porosity, where lithology (210) is expressed in the form of a percentage graph for use to identify different types of rock within the formation, where the percentage graph illustrates a percentage of each type of rock at a given depth, porosity (212) is expressed in the form of a curve representation, and shale plasticity (228) is expressed in the form of at least one of the following representations selected from the group consisting of a curve representation, a percentage graph representation, and a band representation, where the curve representation of shale plasticity (228) comprises at least one curve of shale plasticity parameters selected from the group consisting of water content, clay type, and clay volume, and further where shale plasticity is determined from the water content, clay type and clay volume according to a prescribed shale plasticity model, and where the band representation of shale plasticity (228) provides a graphical illustration indicating a discrete area of shale plasticity at a given depth, further where the band representation of shale plasticity is coded, comprising a first code representing an area of low plasticity, another code representing an area of high shale plasticity, and additional codes representing one or more areas of intermediate shale plasticity. 34. Method according to claim 28, characterized in that the bit wear (234) is determined as a function of cumulative work done according to a prescribed bit wear model (156) and expressed in the form of at least one of the following representations, selected from the group consisting of curve representation and percentage graph representation, where the curve representation (236) of bit wear (234) comprises bit work expressed as a specific energy level at the bit, cumulative work done by the bit, and optional work loss due to grinding, and the percentage graph representation indicates the wear state of the bit at a given depth, further where the percentage graph representation of drill bit wear is coded, comprising a code representing consumed bit life, and another code representing remaining bit life. 35. Method according to claim 28, characterized in that the drill bit's mechanical efficiency (244) is determined as a function of torque/weight on the bit signature for the given drill bit according to a prescribed mechanical efficiency model (152), and expressed in terms of at least one of the following representations selected from the group consisting of a curve representation and a percentage graph representation, where the curve representation (246) of the drill bit's mechanical efficiency (244) includes total torque and cutting torque at the drill bit, and the percentage graph representation of the drill bit's mechanical efficiency (244) graphically illustrates total torque, total torque comprising cutting torque and friction torque components, and further where the percentage graph representation of the bit's mechanical efficiency is coded, comprising a first code to illustrate cutting torque, a second code to illustrate friction-unlimited torque, and a third code to illustrate friction-limited a torque. 36. Method according to claim 35, characterized in that mechanical efficiency (244) is further represented in the form of a percentage graph that illustrates the drilling system's operational limitations (168) that have an adverse effect on mechanical efficiency, where the drilling system's operational limitations (168) correspond to limitations that result in that friction-limited torque occurs, where percentage graph to further indicate a corresponding percentage of impact that each constraint type has on friction-limited torque components of the mechanical efficiency at a given depth, where drilling system operational constraints may include maximum torque on the bit (TOP), maximum weight on the bit ( WOB), minimum and maximum drill cone revolutions per minute (RPM), maximum rate of penetration (ROP) in any combination, and an unconstrained condition, and where the percent graph representation of the drilling system's operating limitations on mechanical efficiency is coded, comprising various k oder to identify various constraints. 37. Method according to claim 28, characterized in that effect is expressed in the form of at least one of the following representations selected from the group consisting of a curve representation and a percentage graph representation, where the curve representation (260) for effect (258) comprises effect limit and operational effect level, where the effect limit corresponds to a maximum power to be supplied to the drill bit, and the operational power level comprises at least one of the following, selected from the group consisting of limited operational power level, recommended operational power level, and predicted operational power level, and wherein the percentage graph representation of power (258) illustrates drilling system operational limitations that have an adverse effect on the power , where the drilling system operating limitations correspond to the limitations resulting in loss of power, the power limitation percentage graph to further indicate a corresponding percentage of impact that each limitation has on the power at a given depth, further where the percentage graph representation of the boresys the theme's operational limitations on power are coded, comprising different codes to identify different limitations. 38. Method according to claim 22, characterized in that it further comprises generating a display (200) of details of proposed drilling equipment (276) together with the geological characteristics (202) and predicted drilling mechanics (204), where the proposed drilling equipment comprises at least one recommended drill bit selection used to predict the performance of the drilling system. 39. Method according to claim 38, characterized in that the first (270) and second (272) drill bit selections are recommended for use in a predicted performance of the drilling of the well hole, and further where the first (270) and second (272) drill bit selections are identified with respective first (276) and second (278) identification numbers, where the first and second identification numbers are shown with the geology characteristic (202) and predicted drilling mechanics (204), further where the location of the first and second identification numbers on the display is chosen to correspond to areas of the predicted performance to which the first and second bit choices respectively apply. 40. Method according to claim 22, characterized in that it further comprises indicating that a change in drill bit selection (280) from a first recommended drill bit selection (270) to a second recommended drill bit selection (272) is necessary at a given depth on the display of geology character stake ( 202) and predicted drilling mechanics (204). 41. A computer program stored on a computer readable medium for executing a computer (50) to predict the performance of a drilling system (10) in drilling a well hole (14) in a given formation (24), the computer program comprising instructions for generating a geological character plot (202) of the formation per depth unit according to a prescribed geological model (142), and issuing signals representing the geological characteristic (202), characterized in that the geological characteristic comprises at least rock strength (216), instructions for obtaining specifications (270 ) of proposed drilling equipment (276) for use in drilling the wellbore, wherein the specifications (270) comprise at least one drill bit specification of a recommended drill bit (276), instructions for determining a predicted drilling mechanics (204) in response to the specification of proposed drilling equipment (270) ) as a function of geology grade (202) per unit depth according to a drilling mechanics model (144), and to output signals representing the predicted drilling mechanics (204), wherein the predicted drilling mechanics comprises at least one of the following selected from the group consisting of bit wear (234), mechanical efficiency (244), power (258), and operational parameters (264), instructions to control a control parameter (66) in drilling the wellbore (14) with the drilling system (10) in response to a predicted drilling mechanics output signal, the control parameter comprising at least one selected from the group consisting of bit weight, RPM, pump flow rate, and hydraulics, instructions for obtaining a measurement parameter (104) in real time during the drilling of the wellbore, and instructions for history fitting (108) of the measurement parameters with back-calculated value of the measurement parameter, wherein the back-calculated value of the measurement parameters is a function of at least one of the following selected from the group consisting of drilling mechanics model and at least one control parameter, and the aforementioned instructions for controlling the control parameter further include instructions operations responsive to a prescribed deviation between the measured parameter and the back-calculated value of the measured parameter, to perform at least one of the following, selected from the group consisting of a) adjusting the drilling mechanics model (144), b) modifying control of a control parameter (116), and c) execution of alarm operation. 42. Computer program according to claim 41, characterized in that it further comprises instructions for generating a display of geological characteristics (202) and predicted drilling mechanics (204) per depth unit in response to geological characteristic output signals and the predicted drilling mechanics output signals. 43. Computer program according to claim 42, characterized in that the generation of a display (200) comprises the use of at least one of the following, selected from the group consisting of a) a display monitor and b) a printer, where the display of geology characterizing and predicted drilling mechanics per depth unit includes one printout. 44. Computer program according to claim 41, characterized in that generation of the geological characteristic (202) comprises the generation of at least one of the following additional character pieces selected from the group consisting of logging data (208), lithology (210), porosity (212) and shale plasticity (228) . 45. Computer program according to claim 41, characterized in that retrieval of the proposed drilling equipment input specifications (270) further comprises retrieval of at least one further specification of proposed drilling equipment selected from the group consisting of borehole motor, top drive motor, rotary drilling motor, mud system, and mud pump. 46. Computer program according to claim 41, characterized in that the operating parameters (270) comprise at least one of the following, selected from the group consisting of weight of the drill bit, drill bit RPM (revolutions per minute), cost, penetration rate, and torque. 47. Computer program according to claim 46, characterized in that the penetration rate (188) comprises instantaneous penetration rate (ROP) and average penetration rate (ROP-avg). 48. Computer program according to claim 42, characterized in that displaying the geological characteristic (202) comprises displaying at least one graphic representation selected from the group consisting of a curve representation, a percentage graph representation and a band representation, and displaying the predicted drilling mechanics (204) comprises displaying at least one graphical representation selected from the group consisting of a curve representation, a percentage graph representation, and a band representation. 49. Computer program according to claim 48, characterized in that the generation of a display (200) comprises the use of at least one of the following, selected from the group consisting of a) a display monitor and b) a printer, where the display of the geological characteristics and predicted drilling mechanics per depth unit includes a printout. 50. Computer program according to claim 48, characterized in that at least one graphical representation of the geological characteristic (202) and at least one graphical representation of the predicted drilling mechanics (204) are color coded.