CN114370264B - Mechanical drilling speed determination and drilling parameter optimization method and device and electronic equipment - Google Patents

Mechanical drilling speed determination and drilling parameter optimization method and device and electronic equipment Download PDF

Info

Publication number
CN114370264B
CN114370264B CN202210025176.7A CN202210025176A CN114370264B CN 114370264 B CN114370264 B CN 114370264B CN 202210025176 A CN202210025176 A CN 202210025176A CN 114370264 B CN114370264 B CN 114370264B
Authority
CN
China
Prior art keywords
drilling
parameter values
parameter
drilling speed
rate
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202210025176.7A
Other languages
Chinese (zh)
Other versions
CN114370264A (en
Inventor
黄文君
任传杰
高德利
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
China University of Petroleum Beijing
Original Assignee
China University of Petroleum Beijing
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by China University of Petroleum Beijing filed Critical China University of Petroleum Beijing
Priority to CN202210025176.7A priority Critical patent/CN114370264B/en
Publication of CN114370264A publication Critical patent/CN114370264A/en
Application granted granted Critical
Publication of CN114370264B publication Critical patent/CN114370264B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • E—FIXED CONSTRUCTIONS
    • E21—EARTH OR ROCK DRILLING; MINING
    • E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B47/00—Survey of boreholes or wells
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH OR ROCK DRILLING; MINING
    • E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B45/00—Measuring the drilling time or rate of penetration
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/02—Agriculture; Fishing; Forestry; Mining
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G06N20/10—Machine learning using kernel methods, e.g. support vector machines [SVM]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G06N20/20—Ensemble learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Mining & Mineral Resources (AREA)
  • Business, Economics & Management (AREA)
  • Theoretical Computer Science (AREA)
  • Geology (AREA)
  • Economics (AREA)
  • Human Resources & Organizations (AREA)
  • Strategic Management (AREA)
  • General Physics & Mathematics (AREA)
  • General Life Sciences & Earth Sciences (AREA)
  • Tourism & Hospitality (AREA)
  • General Business, Economics & Management (AREA)
  • Marketing (AREA)
  • Software Systems (AREA)
  • Fluid Mechanics (AREA)
  • Environmental & Geological Engineering (AREA)
  • Geochemistry & Mineralogy (AREA)
  • Quality & Reliability (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Evolutionary Computation (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Mathematical Physics (AREA)
  • Geophysics (AREA)
  • Data Mining & Analysis (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Artificial Intelligence (AREA)
  • Operations Research (AREA)
  • Medical Informatics (AREA)
  • Game Theory and Decision Science (AREA)
  • Development Economics (AREA)
  • Agronomy & Crop Science (AREA)
  • Animal Husbandry (AREA)
  • Marine Sciences & Fisheries (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Earth Drilling (AREA)

Abstract

The specification discloses a method and a device for determining a mechanical drilling rate and optimizing drilling parameters and electronic equipment, and relates to the technical field of petroleum and natural gas drilling, wherein the method for determining the mechanical drilling rate comprises the following steps: acquiring parameter values of a plurality of drilling parameters in a target work area; substituting parameter values of a plurality of drilling parameters into a mechanical drilling speed equation to calculate and obtain a first mechanical drilling speed; substituting parameter values of a plurality of drilling parameters into a preset prediction model to predict to obtain a drilling speed error; and correcting the first mechanical drilling speed through the drilling speed error to obtain a second mechanical drilling speed, and taking the second mechanical drilling speed as a target mechanical drilling speed. The method for determining the mechanical drilling speed can make up the influence of the drilling parameters which are not mentioned in the mechanical drilling speed equation on the mechanical drilling speed, and can also make up the error value between the calculation result of the mechanical drilling speed equation and the actual mechanical drilling speed, so that the finally determined mechanical drilling speed has higher precision and higher accuracy, and the drilling parameter optimization method based on the mechanical drilling speed determination method has higher accuracy.

Description

Mechanical drilling speed determination and drilling parameter optimization method and device and electronic equipment
Technical Field
The application relates to the technical field of petroleum and natural gas drilling, in particular to a method and a device for determining mechanical drilling speed and optimizing drilling parameters and electronic equipment.
Background
The rate of penetration refers to the length of drilling per unit time (i.e., unit footage). The rate of penetration is affected by a variety of drilling factors, such as weight on bit, rotational speed, formation conditions, etc. The well drilling parameter optimization refers to researching the influence of each controllable well drilling condition on the mechanical drilling speed under the objective condition of a target work area, and determining the numerical value of each controllable parameter when the objective function can obtain the maximum value. In the process of optimizing drilling parameters, the accuracy of the prediction of the rate of penetration is very important.
The existing mechanical drilling speed prediction method is based on a drilling speed equation established by introducing a small amount of drilling parameters, based on a large amount of on-site statistics and processing by applying various mathematical methods. That is, the existing method for predicting the rate of mechanical drilling determines each parameter according to the actual drilling data, establishes a prediction equation of the rate of mechanical drilling, and inputs the current drilling parameters to predict the rate of mechanical drilling. The most widely used mechanical drilling rate prediction equation at present is the modified young drilling rate equation:
Wherein v is the rate of penetration; k is the stratum drillability coefficient and is related to the mechanical property of stratum rock, the type of drill bit, the performance of drilling fluid and the like; c (C) P Is the differential pressure influence coefficient; c (C) H Is the hydraulic parameter influence coefficient; w is the weight on bit; w (W) 0 Is threshold weight on bit; n is the rotation speed; b is a rotation speed index; c (C) 2 Is the tooth wear coefficient; h is the amount of tooth wear.
The steps for determining each parameter according to the actual drilling data are as follows: firstly, determining a threshold weight-on-bit W according to a five-point method drilling speed experiment 0 And a rotation speed index b; determining a stratum drillability coefficient K according to trial drilling data of the new drill bit; and then determining the rock abrasiveness coefficient and the tooth abrasiveness coefficient of the rock stratum drilled by the drill bit according to the work group record of the drill bit.
It can be seen that the existing rate of penetration equations only consider a small number of work area drilling parameters, however, the target work area environment is more complex, and more work area drilling parameters that can affect the rate of penetration are not considered. In addition, model parameters are mutually connected and coupled, and some parameters have large discreteness (such as rock property parameters, actual weight of a drill bit in a deep well or a well track, a horizontal well and a large displacement well) or even are difficult to determine. These factors result in lower accuracy in the predicted rate of penetration of the existing rate of penetration prediction methods.
Disclosure of Invention
The embodiment of the application aims to provide a method and a device for determining the mechanical drilling speed and optimizing drilling parameters and electronic equipment, so as to solve the problem of low accuracy of the traditional mechanical drilling speed prediction.
To solve the above technical problem, a first aspect of the present specification provides a method for determining a rate of penetration, including: acquiring parameter values of a plurality of drilling parameters in a target work area; substituting the parameter values of the drilling parameters into a mechanical drilling speed equation, and calculating to obtain a first mechanical drilling speed; substituting the parameter values of the drilling parameters into a preset prediction model, and predicting to obtain a drilling rate error; and correcting the first mechanical drilling speed through the drilling speed error to obtain a second mechanical drilling speed, and taking the second mechanical drilling speed as a target mechanical drilling speed.
In some embodiments, substituting the values of the plurality of drilling parameters into a preset prediction model, and before predicting to obtain the drilling rate error, further includes: obtaining a plurality of groups of sample parameter values of a plurality of drilling parameters of a target work area, wherein each group of sample parameter values comprises a mechanical drilling speed sample value and sample values of corresponding drilling parameters; for each set of sample parameter values, the following operations are performed to train the predictive model: substituting the sample values of all drilling parameters in the current set of sample parameter values into the mechanical drilling speed equation, and calculating to obtain a first mechanical drilling speed; calculating a difference between the sample value of the rate of penetration and the first rate of penetration as a rate of penetration error; and training the prediction model by taking the drilling speed error as the output of the prediction model and taking the sample value of each drilling parameter in the current set of sample parameter values as the input of the prediction model.
In some embodiments, the rate of penetration equation is:wherein ROP represents the rate of penetration;coefficient a 1 Representing the effect of formation strength on the rate of penetration; />Coefficient a 2 Indicating the effect of formation compaction on the rate of penetration, D indicating the drilling depth; />Coefficient a 3 Indicating the effect of formation undercompacting on the rate of penetration, TVD indicating the sag, g p Representing formation pressure, ECD represents the density of the circulating drilling fluid; />Coefficient a 4 Representing the effect of the bottom hole differential pressure on the mechanical drilling speed; />Coefficient a 5 Representing the effect of weight on the rate of penetration, W representing weight on bit, D b Indicating the diameter of the drill bit, t is a subscript, ++>Representing the ratio of minimum weight on bit to bit diameter required to break rock; />Coefficient a 6 The influence of the rotation speed on the mechanical drilling speed is shown, and N is the rotation speed; />Coefficient a 7 Indicating the influence of drill bit abrasion on the mechanical drilling speed, wherein h indicates the drill bit abrasion amount; />Coefficient a 8 The effect of bit hydraulics on the rate of penetration is expressed, ρ is the density of the drilling fluid, q is the flow rate of the drilling fluid injected, μ is the apparent viscosity of the drilling fluid, d n Indicating the drill bit nozzle diameter.
A second aspect of the present specification provides a method of optimizing drilling parameters, comprising: acquiring a plurality of controllable parameters of a target work area and a value range of the controllable parameters; generating a plurality of groups of parameter values according to the value range of each controllable parameter, and respectively calculating a second mechanical drilling speed corresponding to each group of parameter values; wherein, each group of parameter values comprises parameter values of the controllable parameters, and the second mechanical drilling speed corresponding to one group of parameter values is obtained according to the following method: substituting the parameter values of each controllable parameter in the set of parameter values into a mechanical drilling speed equation, and calculating to obtain a first mechanical drilling speed; substituting the parameter values of each controllable parameter in the group of parameter values into a preset prediction model, and predicting to obtain a drilling rate error; correcting the first mechanical drilling speed through the drilling speed error to obtain a second mechanical drilling speed; and taking the parameter value of each controllable parameter in a group of parameter values corresponding to the maximum value of the second mechanical drilling speed as the optimal drilling parameter value.
In some embodiments, obtaining a plurality of controllable parameters of the target work area and a value range of each controllable parameter includes: acquiring a plurality of hydraulic parameters of a target work area and a value range of each hydraulic parameter, wherein the hydraulic parameters comprise at least one of the following: drilling fluid density, apparent viscosity of drilling fluid, diameter of drill bit nozzle, flow rate of injected drilling fluid.
In some embodiments, generating a plurality of groups of parameter values according to the value range of each controllable parameter, and respectively calculating a second mechanical drilling speed corresponding to each group of parameter values; taking the parameter value of each controllable parameter in a group of parameter values corresponding to the maximum value of the second mechanical drilling speed as the optimal drilling parameter value, wherein the method comprises the following steps: setting a predetermined number of variables; generating the preset number of groups of parameter values according to the value range of each controllable parameter, wherein each group of parameter values comprises parameter values of the plurality of controllable parameters; assigning a set of parameter values to each variable, and calculating a second rate of penetration corresponding to the assigned set of parameter values for each variable; taking a variable corresponding to the maximum value of the second mechanical drilling speed as an optimal variable; the following steps are circularly executed until a preset cycle termination condition is reached, and the parameter value of each controllable parameter in a group of parameter values corresponding to the optimal variable is used as the optimal drilling parameter: according to the current optimal variable and the preset adjustment amplitude of each controllable parameter, each variable is adjusted according to the following method: carrying out multiple times of adjustment on the variable to obtain a plurality of groups of parameter values, wherein each time of adjustment is based on a group of parameter values currently corresponding to the variable, and adjusting the parameter value of at least one controllable parameter in the group of parameter values currently corresponding to the variable; calculating the second mechanical drilling speed corresponding to each set of parameter values obtained through adjustment, and taking a set of parameter values corresponding to the maximum value of the second mechanical drilling speed as a set of parameter values corresponding to the adjusted variables; calculating a second mechanical drilling rate corresponding to a group of parameter values corresponding to each adjusted variable; and taking the adjusted variable corresponding to the maximum value of the second mechanical drilling speed as an optimal variable.
A third aspect of the present specification provides a rate of penetration determining apparatus comprising: the first acquisition unit is used for acquiring parameter values of a plurality of drilling parameters in the target work area; the first calculation unit is used for substituting the parameter values of the drilling parameters into a mechanical drilling speed equation to calculate and obtain a first mechanical drilling speed; the prediction unit is used for substituting the parameter values of the drilling parameters into a preset prediction model to predict and obtain drilling speed errors; and the correction unit is used for correcting the first mechanical drilling speed through the drilling speed error to obtain a second mechanical drilling speed, and taking the second mechanical drilling speed as a target mechanical drilling speed.
In some embodiments, substituting the values of the plurality of drilling parameters into a preset prediction model, and before predicting to obtain the drilling rate error, further includes: a second obtaining unit, configured to obtain a plurality of sets of sample parameter values of a plurality of drilling parameters of a target work area, where each set of sample parameter values includes a sample value of a rate of penetration and a sample value of each drilling parameter corresponding to the sample value; a training unit for performing, for each set of sample parameter values, the following operations to train the predictive model: substituting the sample values of all drilling parameters in the current set of sample parameter values into the mechanical drilling speed equation, and calculating to obtain a first mechanical drilling speed; calculating a difference between the sample value of the rate of penetration and the first rate of penetration as a rate of penetration error; and training the prediction model by taking the drilling speed error as the output of the prediction model and taking the sample value of each drilling parameter in the current set of sample parameter values as the input of the prediction model.
In some embodiments, the rate of penetration equation is:wherein ROP represents the rate of penetration;coefficient a 1 Representing a formationInfluence of strength on the rate of penetration; />Coefficient a 2 Indicating the effect of formation compaction on the rate of penetration, D indicating the drilling depth; />Coefficient a 3 Indicating the effect of formation undercompacting on the rate of penetration, TVD indicating the sag, g p Representing formation pressure, ECD represents the density of the circulating drilling fluid; />Coefficient a 4 Representing the effect of the bottom hole differential pressure on the mechanical drilling speed; />Coefficient a 5 Representing the effect of weight on the rate of penetration, W representing weight on bit, D b Indicating the diameter of the drill bit, t is a subscript, ++>Representing the ratio of minimum weight on bit to bit diameter required to break rock; />Coefficient a 6 The influence of the rotation speed on the mechanical drilling speed is shown, and N is the rotation speed; />Coefficient a 7 Indicating the influence of drill bit abrasion on the mechanical drilling speed, wherein h indicates the drill bit abrasion amount; />Coefficient a 8 The effect of bit hydraulics on the rate of penetration is expressed, ρ is the density of the drilling fluid, q is the flow rate of the drilling fluid injected, μ is the apparent viscosity of the drilling fluid, d n Indicating the drill bit nozzle diameter.
A fourth aspect of the present specification provides a drilling parameter optimization apparatus comprising: the third acquisition unit is used for acquiring a plurality of controllable parameters and the value ranges of the controllable parameters of the target work area; the generating unit is used for generating a plurality of groups of parameter values according to the value range of each controllable parameter, and respectively calculating a second mechanical drilling speed corresponding to each group of parameter values; wherein, each group of parameter values comprises parameter values of the controllable parameters, and the second mechanical drilling speed corresponding to one group of parameter values is obtained according to the following method: substituting the parameter values of each controllable parameter in the set of parameter values into a mechanical drilling speed equation, and calculating to obtain a first mechanical drilling speed; substituting the parameter values of each controllable parameter in the group of parameter values into a preset prediction model, and predicting to obtain a drilling rate error; correcting the first mechanical drilling speed through the drilling speed error to obtain a second mechanical drilling speed; and the determining unit is used for taking the parameter value of each controllable parameter in a group of parameter values corresponding to the maximum value of the second mechanical drilling speed as the optimal drilling parameter value.
In some embodiments, the third acquisition unit comprises: an acquisition subunit, configured to acquire a plurality of hydraulic parameters of a target work area and a value range of each hydraulic parameter, where the hydraulic parameters include at least one of: drilling fluid density, apparent viscosity of drilling fluid, diameter of drill bit nozzle, flow rate of injected drilling fluid.
In some embodiments, the generating unit and the determining unit comprise: a setting subunit for setting a predetermined number of variables; a generating subunit, configured to generate the predetermined number of sets of parameter values according to a value range of each controllable parameter, where each set of parameter values includes parameter values of the plurality of controllable parameters; a calculating subunit, configured to allocate a set of parameter values to each variable, and calculate a second rate of penetration corresponding to the set of parameter values allocated to each variable; the determining subunit is used for taking a variable corresponding to the maximum value of the second mechanical drilling speed as an optimal variable; the adjusting subunit is used for adjusting each variable according to the current optimal variable and the preset adjusting amplitude of each controllable parameter according to the following method: carrying out multiple times of adjustment on the variable to obtain a plurality of groups of parameter values, wherein each time of adjustment is based on a group of parameter values currently corresponding to the variable, and adjusting the parameter value of at least one controllable parameter in the group of parameter values currently corresponding to the variable; calculating the second mechanical drilling speed corresponding to each set of parameter values obtained through adjustment, and taking a set of parameter values corresponding to the maximum value of the second mechanical drilling speed as a set of parameter values corresponding to the adjusted variables; the calculating subunit is further used for calculating a second mechanical drilling speed corresponding to a group of parameter values corresponding to each adjusted variable; the determining subunit is further configured to use the adjusted variable corresponding to the maximum value of the second mechanical drilling speed as an optimal variable; and the adjusting subunit, the calculating subunit and the determining subunit execute the loop until a preset loop termination condition is reached, and the determining subunit takes the parameter value of each controllable parameter in a group of parameter values corresponding to the optimal variable as the optimal drilling parameter.
A fifth aspect of the present specification provides an electronic device, comprising: the system comprises a memory and a processor, wherein the processor and the memory are in communication connection, the memory stores computer instructions, and the processor realizes the steps of the method in the first aspect or the second aspect by executing the computer instructions.
A sixth aspect of the present description provides a computer storage medium storing computer program instructions which, when executed, implement the steps of the method of any one of the first or second aspects.
In the method for determining the mechanical drilling speed, since the prediction model is obtained by training a large number of training samples, the prediction model characterizes rules between a plurality of drilling parameter values and the mechanical drilling speed, which are reflected by a large number of data, and the rules are the results of the synergistic effect of the drilling parameters, so that the influence of the drilling parameters which are not mentioned in the mechanical drilling speed equation on the mechanical drilling speed can be compensated, and the error value between the calculation result of the mechanical drilling speed equation and the actual mechanical drilling speed can be compensated for the drilling parameters mentioned in the mechanical drilling speed equation. The drilling speed error is obtained through a prediction model, and the prediction model is obtained through a large amount of data rules, so that the drilling speed error has certain accuracy.
In the above-mentioned method of the rate of penetration, the first rate of penetration is obtained by substituting a plurality of drilling parameters of the target work area into a rate of penetration equation, and the rate of penetration equation is obtained by a mechanism of influence of each drilling parameter on the rate of penetration, so that the actual rate of penetration is approximated by the first rate of penetration. According to the method for obtaining the second mechanical drilling speed by correcting the first mechanical drilling speed through the drilling speed error with certain accuracy, the mechanical drilling speed is taken as the target mechanical drilling speed, and the first mechanical drilling speed is relatively close to the actual mechanical drilling speed, and the drilling speed error has certain prediction accuracy, so that the difference between the corrected second mechanical drilling speed and the actual mechanical drilling speed is further reduced, and the prediction result is more accurate.
On the other hand, since the first rate of penetration obtained by the rate of penetration equation is already close to the true rate of penetration, the magnitude of the rate of penetration error is typically much smaller than the magnitude of the first rate of penetration, which also results in a higher accuracy of the rate of penetration error and thus a higher accuracy of the second rate of penetration.
The drilling parameter optimization method optimizes the drilling parameters based on the mechanical drilling speed determination method, and the accuracy of the drilling parameter optimization method is higher because the mechanical drilling speed determination method is higher.
According to the drilling parameter optimization method, the influence of various controllable parameters on the mechanical drilling speed is comprehensively considered, and the drilling parameters can be optimized for different well sections and different drilling tool combinations, so that the mechanical drilling speed is improved, the drilling tool combinations can be guided to be optimized, the drilling parameter is optimized and analyzed, and the like, and the method is convenient to apply to a target work area.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are necessary for the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the following description are only some of the embodiments described in the application, and that other drawings can be obtained from these drawings without inventive effort for a person skilled in the art.
FIG. 1 illustrates a flow chart of one embodiment of a method of determining a rate of penetration provided herein;
FIG. 2 shows a flow chart of a method of training a predictive model provided herein;
FIG. 3 shows the comparison between the predicted rate of penetration of the method and the theoretical model predicted value calculated from the rate of penetration measurement and rate of penetration equation for a target work area;
FIG. 4 illustrates a flow chart of one embodiment of a method of optimizing drilling parameters provided herein;
FIG. 5 illustrates a flow chart of a method provided herein for determining a maximum value of a second rate of penetration and its corresponding parameter values;
FIG. 6 illustrates a weight on bit-rotation chart obtained according to the drilling parameter optimization method provided herein;
FIG. 7 shows a functional block diagram of the rate of penetration determination apparatus provided herein;
FIG. 8 shows a functional block diagram of the drilling parameter optimization apparatus provided herein;
fig. 9 shows a functional block diagram of an electronic device provided in the present specification.
Detailed Description
In order to make the technical solution of the present application better understood by those skilled in the art, the technical solution of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, but not all embodiments of the present application. All other embodiments, based on the embodiments of the application, which would be apparent to one of ordinary skill in the art without undue burden are intended to be within the scope of the application.
In order to solve the problem of low accuracy of the existing mechanical drilling rate prediction method, the specification provides a mechanical drilling rate determination method, as shown in fig. 1, comprising the following steps:
s110: parameter values of a plurality of drilling parameters of a target work area are obtained.
Drilling parameters of the target work area include both controllable parameters of the rate of penetration and uncontrollable parameters of the rate of penetration.
The controllable parameters of the mechanical drilling speed are parameters which can control the value of the mechanical drilling speed in a target work area and change of the mechanical drilling speed can influence the value of the mechanical drilling speed. For example, the controllable parameter may be a pressure applied by the drill bit during drilling (abbreviated as weight on bit), a rotational speed of the drill bit during drilling (abbreviated as rotational speed), a flow rate of drilling fluid injected during drilling, and the like. The controllable parameters can also be hydraulic parameters such as drilling fluid density, drill bit nozzle diameter, injected drilling fluid flow rate and the like. The inventors have also proposed that the apparent viscosity of the drilling fluid is also a controllable parameter.
The uncontrollable parameters of the mechanical drilling rate refer to parameters of which the value can not be controlled in the drilling process. For example, the uncontrollable parameters may be parameters that are not capable of being changed, such as rock compressive strength, formation pressure gradient, etc., or drilling restriction parameters that are not capable of being changed at will may be pre-designed for the angle of well deviation, well depth, vertical depth, etc.
Before step S110, the type of drilling parameter needs to be determined.
In some embodiments, the type of drilling parameters that can affect the rate of penetration may be determined empirically by an expert in the target work area.
In some embodiments, all types of drilling parameters that can be collected or analyzed by the target site may be considered, and drilling parameters that can affect the rate of penetration may be selected from these types of drilling parameters by a screening method. This allows screening out types of drilling parameters that are empirically imperceptible to the expert and that can affect the rate of penetration. Specifically, values of some mechanical drilling rates and values of all drilling parameters corresponding to the values of each mechanical drilling rate can be obtained, data are preprocessed, null values and abnormal values are deleted, semantic coding is carried out on each parameter type, and feature selection is carried out on the drilling parameters by utilizing a principal component analysis method, so that the drilling parameter types capable of influencing the mechanical drilling rate are obtained. For example, by the method, drilling parameters such as weight on bit, rotation speed, displacement, torque, well depth, vertical depth, well Duan Leixing, stratum type, guiding drilling tool type, drill bit type, drilling time, mechanical drilling speed and the like can be selected from parameter types such as weight on bit, rotation speed, displacement, torque, vertical depth, well section type, guiding drilling tool type, drilling time and the like. The parameters are selected as the drilling parameters to be acquired in step S110.
S120: substituting parameter values of a plurality of drilling parameters into a mechanical drilling speed equation, and calculating to obtain a first mechanical drilling speed.
The mechanical drilling speed equation can be any mechanical drilling speed equation, which can be existing in the prior art, can be improved on the basis of the existing mechanical drilling speed equation, and can be a newly proposed mechanical drilling speed equation. The mechanical drilling speed equation gives the quantitative relation between a plurality of drilling parameters and the mechanical drilling speed in the form of a formula, and characterizes the influence mechanism of each drilling parameter on the mechanical drilling speed.
For example, in some embodiments, the rate of penetration equation may be
Wherein v is the rate of penetration; k is the stratum drillability coefficient and is related to the mechanical property of stratum rock, the type of drill bit, the performance of drilling fluid and the like; c (C) P Is the differential pressure influence coefficient; c (C) H Is the hydraulic parameter influence coefficient; w is the weight on bit; w (W) 0 Is threshold weight on bit; n is the rotation speed; b is a rotation speed index; c (C) 2 Is the tooth wear coefficient; h is the amount of tooth wear.
For another example, in some embodiments, the rate of penetration equation may be:wherein ROP represents the rate of penetration; />Coefficient a 1 Representing the effect of formation strength on the rate of penetration; />Coefficient a 2 Indicating the effect of formation compaction on the rate of penetration, D indicating the drilling depth; />Coefficient a 3 Indicating the effect of formation undercompacting on the rate of penetration, TVD indicating the sag, g p Representing formation pressure, ECD represents the density of the circulating drilling fluid;coefficient a 4 Representing the effect of the bottom hole differential pressure on the mechanical drilling speed; />Coefficient a 5 Representing the effect of weight on the rate of penetration, W representing weight on bit, D b Indicating the diameter of the drill bit, t is a subscript, ++>Representing the ratio of minimum weight on bit to bit diameter required to break rock; />Coefficient a 6 The influence of the rotation speed on the mechanical drilling speed is shown, and N is the rotation speed; />Coefficient a 7 Indicating the influence of drill bit abrasion on the mechanical drilling speed, wherein h indicates the drill bit abrasion amount;coefficient a 8 The effect of bit hydraulics on the rate of penetration is expressed, ρ is the density of the drilling fluid, q is the flow rate of the drilling fluid injected, μ is the apparent viscosity of the drilling fluid, d n Indicating the straight nozzle of the drill bitAnd (3) diameter.
S130: substituting parameter values of a plurality of drilling parameters into a preset prediction model, and predicting to obtain drilling speed errors.
The preset prediction model can be in the forms of a neural network model, a support vector machine, a random forest tree and the like, or can also be in other forms of network models.
Prior to step S130, a method of training the predictive model based on the training samples may also be included. For example, as shown in fig. 2, the training method includes the steps of:
S210: a plurality of sets of sample parameter values for a plurality of drilling parameters of a target work area are obtained, wherein each set of sample parameter values includes a sample value of a rate of penetration and a corresponding sample value of each drilling parameter.
S220: for each set of sample parameter values, the following operations are performed to train the predictive model: substituting the sample values of all drilling parameters in the current set of sample parameter values into a mechanical drilling speed equation, and calculating to obtain a first mechanical drilling speed; calculating a difference between the sample value of the rate of penetration and the first rate of penetration as a rate of penetration error; taking the drilling speed error as the output of the prediction model, taking the sample value of each drilling parameter in the current set of sample parameter values as the input of the prediction model, and training the prediction model.
In some embodiments, pre-trained predictive models may be stored, and the predictive model retrieved from storage every time a predicted rate-of-penetration error is required.
S140: and correcting the first mechanical drilling speed through the drilling speed error to obtain a second mechanical drilling speed, and taking the second mechanical drilling speed as a target mechanical drilling speed.
In the method for determining the mechanical drilling speed, since the prediction model is obtained by training a large number of training samples, the prediction model characterizes rules between a plurality of drilling parameter values and the mechanical drilling speed, which are reflected by a large number of data, and the rules are the results of the synergistic effect of the drilling parameters, so that the influence of the drilling parameters which are not mentioned in the mechanical drilling speed equation on the mechanical drilling speed can be compensated, and the error value between the calculation result of the mechanical drilling speed equation and the actual mechanical drilling speed can be compensated for the drilling parameters mentioned in the mechanical drilling speed equation. The drilling speed error is obtained through a prediction model, and the prediction model is obtained through a large amount of data rules, so that the drilling speed error has certain accuracy.
In the above-mentioned method of the rate of penetration, the first rate of penetration is obtained by substituting a plurality of drilling parameters of the target work area into a rate of penetration equation, and the rate of penetration equation is obtained by a mechanism of influence of each drilling parameter on the rate of penetration, so that the actual rate of penetration is approximated by the first rate of penetration. According to the method for obtaining the second mechanical drilling speed by correcting the first mechanical drilling speed through the drilling speed error with certain accuracy, the mechanical drilling speed is taken as the target mechanical drilling speed, and the first mechanical drilling speed is relatively close to the actual mechanical drilling speed, and the drilling speed error has certain prediction accuracy, so that the difference between the corrected second mechanical drilling speed and the actual mechanical drilling speed is further reduced, and the prediction result is more accurate.
On the other hand, since the first rate of penetration obtained by the rate of penetration equation is already close to the true rate of penetration, the magnitude of the rate of penetration error is typically much smaller than the magnitude of the first rate of penetration, which also results in a higher accuracy of the rate of penetration error and thus a higher accuracy of the second rate of penetration.
From the above analysis, the present specification provides a method for further improving accuracy of determination of the rate of penetration based on the rate of penetration equation, that is, a data-mechanism fusion rate of penetration determination method, in which the data refers to the error prediction method and the mechanism refers to the first rate of penetration determination method.
FIG. 3 shows the comparison between the predicted rate of penetration of the method for a target work area and the theoretical model predicted value calculated from the rate of penetration measurement and rate of penetration equation. As can be seen from fig. 3, the prediction accuracy of the mechanical drilling rate can be greatly improved by the mechanical drilling rate prediction method, and the prediction accuracy applied to the target work area is higher than 95% according to actual data calculation.
Based on the above-mentioned mechanical drilling rate method, a drilling parameter optimization method can be further provided. For example, the drilling parameters may be optimized with the minimum value of the unit footage cost as a target, or with the maximum value of the rate of penetration as a target.
The present specification targets the maximum value of the mechanical drilling rate, and provides a drilling parameter optimization method, as shown in fig. 4, which includes the following steps:
s410: and acquiring a plurality of controllable parameters of the target work area and the value range of the controllable parameters.
Drilling parameters of the target work area include both controllable parameters of the rate of penetration and uncontrollable parameters of the rate of penetration.
The controllable parameters of the mechanical drilling speed refer to parameters of which the value can be controlled in a target work area (namely, the value of the parameters can be controlled), and the change of the value can influence the value of the mechanical drilling speed. For example, the controllable parameter may be a pressure applied by the drill bit during drilling (abbreviated as weight on bit), a rotational speed of the drill bit during drilling (abbreviated as rotational speed), a flow rate of drilling fluid injected during drilling, and the like. The controllable parameters can also be hydraulic parameters such as drilling fluid density, drill bit nozzle diameter, injected drilling fluid flow rate and the like. The inventors have also proposed that the apparent viscosity of the drilling fluid is also a controllable parameter.
The uncontrollable parameters of the mechanical drilling rate refer to parameters of which the value can not be controlled in the drilling process. For example, the uncontrollable parameters may be parameters that are not capable of being changed, such as rock compressive strength, formation pressure gradient, etc., or drilling restriction parameters that are not capable of being changed at will may be pre-designed for the angle of well deviation, well depth, vertical depth, etc.
The range of values of the controllable parameters is typically determined by equipment or target site conditions constraints.
S420: generating a plurality of groups of parameter values according to the value range of each controllable parameter, and respectively calculating a second mechanical drilling speed corresponding to each group of parameter values; wherein, each group of parameter values comprises parameter values of a plurality of controllable parameters, and the second mechanical drilling speed corresponding to one group of parameter values is obtained according to the following method: substituting parameter values of each controllable parameter in a group of parameter values into a mechanical drilling speed equation, and calculating to obtain a first mechanical drilling speed; substituting parameter values of each controllable parameter in a group of parameter values into a preset prediction model, and predicting to obtain a drilling rate error; and correcting the first mechanical drilling speed through the drilling speed error to obtain a second mechanical drilling speed.
The difference between the parameter values of different groups can be the difference of the value of one controllable parameter or the difference of the value of a plurality of controllable parameters.
The calculation method of the second drilling rate corresponding to the set of parameter values may refer to the drilling rate determination method shown in fig. 1. Although the method of optimizing drilling parameters shown in fig. 4 aims at optimizing only controllable parameters, in addition to obtaining parameter values of controllable parameters, parameter values of uncontrollable parameters of the target work area are also required to be obtained during the calculation of the second rate of penetration.
S430: and taking the parameter value of each controllable parameter in a group of parameter values corresponding to the maximum value of the second mechanical drilling speed as the optimal drilling parameter value.
In some embodiments, steps S420 and S430 may be performed by determining a plurality of sets of parameter values, calculating a corresponding second rate of penetration for each set of parameter values, and comparing the second rates of penetration to obtain a maximum value, thereby determining a maximum value of the second rate of penetration and a corresponding parameter value thereof.
In some embodiments, steps S420 and S430 described above, the method shown in fig. 5 may also be used to determine the maximum value of the second rate of penetration and its corresponding parameter value.
As shown in fig. 5, the determination method includes the steps of:
s510: a predetermined number of variables are set.
S520: and generating a predetermined number of groups of parameter values according to the value range of each controllable parameter, wherein each group of parameter values comprises parameter values of a plurality of controllable parameters.
S530: and allocating a set of parameter values to each variable, and calculating a second mechanical drilling speed corresponding to the allocated set of parameter values for each variable.
S540: and taking the variable corresponding to the maximum value of the second mechanical drilling speed as the optimal variable.
S550: it is determined whether a predetermined cycle termination condition is reached. If yes, then execute S560; if not, steps S570 to S590 are performed.
S560: and taking the parameter value of each controllable parameter in a group of parameter values corresponding to the optimal variable as the optimal drilling parameter.
S570: according to the current optimal variable and the preset adjustment amplitude of each controllable parameter, each variable is adjusted according to the following method: multiple times of adjustment are carried out on the variable to obtain multiple groups of parameter values, wherein each time of adjustment is based on a group of parameter values corresponding to the variable at present, and the parameter value of at least one controllable parameter in the group of parameter values corresponding to the variable at present is adjusted; and calculating the second mechanical drilling speed corresponding to each set of parameter values obtained through adjustment, and taking the set of parameter values corresponding to the maximum mechanical drilling speed value as the set of parameter values corresponding to the variable after adjustment.
That is, the variable is adjusted with the range of values of the controllable parameters as a constraint.
Specifically, the variables may be adjusted to obtain adjusted particles for use in the next cycle according to the following formula:
v t+1 ＝ωv t +r 1 ·rand()·(P t -x t )+r 2 ·rand()·(G t -x t )
x t+1 ＝x t +v t
wherein: omega is the inertial weight; r is (r) 1 、r 2 Is an acceleration constant; rand () is interval 0,1]Random numbers uniformly distributed on the base; p (P) t For the target variable (i.e. the one with the largest second mechanical drilling rate among the modified multiple parameter values) after the previous cycle adjustment, G t The optimal variable determined for the last cycle. X is x t To adjust the previous variable, v t To adjust the speed x t+1 Is the adjusted variable.
S580: and calculating a second mechanical drilling speed corresponding to a group of parameter values corresponding to each adjusted variable.
S590: and taking the adjusted variable corresponding to the maximum value of the second mechanical drilling speed as an optimal variable, and jumping to S550.
The method for determining the maximum value of the second mechanical drilling speed integrates the idea of a particle swarm optimization algorithm, and can quickly find the maximum value of the second mechanical drilling speed under the condition of more variables, thereby improving the response speed of drilling parameter optimization.
The drilling parameter optimization method optimizes the drilling parameters based on the mechanical drilling speed determination method, and the accuracy of the drilling parameter optimization method is higher because the mechanical drilling speed determination method is higher.
According to the drilling parameter optimization method, the influence of various controllable parameters on the mechanical drilling speed is comprehensively considered, and the drilling parameters can be optimized for different well sections and different drilling tool combinations, so that the mechanical drilling speed is improved, the drilling tool combinations can be guided to be optimized, the drilling parameter is optimized and analyzed, and the like, and the method is convenient to apply to a target work area.
Taking an A well of a target work area as an example, by inputting different stratum properties, selected drill bit types, drilling fluid properties and other parameters, automatic optimization of drilling pressure and rotating speed is realized according to the drilling parameter optimization method, and a drilling pressure-rotating speed chart is made according to the result, wherein the point on the upper right side in fig. 6 is the optimal mechanical drilling speed, which shows that the highest mechanical drilling speed can be realized under the recommended parameters of 130kN of drilling pressure and 130rpm of rotating speed, as shown in fig. 6.
The present specification provides a rate of penetration determination apparatus that may be used to implement the rate of penetration determination method of the machine shown in fig. 1. As shown in fig. 7, the apparatus includes a first acquisition unit 710, a first calculation unit 720, a prediction unit 730, and a correction unit 740.
The first obtaining unit 710 is configured to obtain parameter values of a plurality of drilling parameters in a target work area.
The first calculating unit 720 is configured to substitute parameter values of a plurality of drilling parameters into a mechanical drilling rate equation, and calculate a first mechanical drilling rate.
The prediction unit 730 is configured to substitute parameter values of a plurality of drilling parameters into a preset prediction model, and predict a drilling rate error.
The correction unit 740 is configured to correct the first rate of penetration by using the rate of penetration error, obtain a second rate of penetration, and take the second rate of penetration as the target rate of penetration.
In some embodiments, the rate of penetration determination apparatus further includes a second acquisition unit 750 and a training unit 760.
The second obtaining unit 750 is configured to obtain a plurality of sets of sample parameter values of a plurality of drilling parameters of the target work area, where each set of sample parameter values includes a sample value of a rate of penetration and a sample value of each drilling parameter corresponding thereto.
The training unit 760 is configured to perform the following operations for each set of sample parameter values to train the prediction model: substituting the sample values of all drilling parameters in the current set of sample parameter values into a mechanical drilling speed equation, and calculating to obtain a first mechanical drilling speed; calculating a difference between the sample value of the rate of penetration and the first rate of penetration as a rate of penetration error; taking the drilling speed error as the output of the prediction model, taking the sample value of each drilling parameter in the current set of sample parameter values as the input of the prediction model, and training the prediction model.
In some embodiments, the rate of penetration equation is:
wherein ROP represents the rate of penetration;coefficient a 1 Representing the effect of formation strength on the rate of penetration; />Coefficient a 2 Indicating the effect of formation compaction on the rate of penetration, D indicating the drilling depth;coefficient a 3 Indicating the effect of formation undercompacting on the rate of penetration, TVD indicating the sag, g p Represents formation pressure and ECD represents circulationThe density of the annulus drilling fluid; />Coefficient a 4 Representing the effect of the bottom hole differential pressure on the mechanical drilling speed; />Coefficient a 5 Representing the effect of weight on the rate of penetration, W representing weight on bit, D b Indicating the diameter of the drill bit, t being indicated as subscript, < ->Representing the ratio of minimum weight on bit to bit diameter required to break rock; />Coefficient a 6 The influence of the rotation speed on the mechanical drilling speed is shown, and N is the rotation speed; />Coefficient a 7 Indicating the influence of drill bit abrasion on the mechanical drilling speed, wherein h indicates the drill bit abrasion amount; />Coefficient a 8 The effect of bit hydraulics on the rate of penetration is expressed, ρ is the density of the drilling fluid, q is the flow rate of the drilling fluid injected, μ is the apparent viscosity of the drilling fluid, d n Indicating the drill bit nozzle diameter.
The details of the above-mentioned device for determining the rate of penetration may be understood by referring to the description and effects related to the corresponding embodiment of fig. 1, and will not be repeated here.
The present disclosure also provides a drilling parameter optimization apparatus that may be used to implement the drilling parameter optimization method shown in fig. 4. As shown in fig. 8, the apparatus includes a third acquisition unit 810, a generation unit 820, and a determination unit 830.
The third obtaining unit 810 is configured to obtain a plurality of controllable parameters and a range of values of the target work area.
The generating unit 820 is configured to generate a plurality of sets of parameter values according to the value ranges of the controllable parameters, and calculate a second mechanical drilling rate corresponding to each set of parameter values respectively; wherein, each group of parameter values comprises parameter values of a plurality of controllable parameters, and the second mechanical drilling speed corresponding to one group of parameter values is obtained according to the following method: substituting parameter values of each controllable parameter in a group of parameter values into a mechanical drilling speed equation, and calculating to obtain a first mechanical drilling speed; substituting parameter values of each controllable parameter in a group of parameter values into a preset prediction model, and predicting to obtain a drilling rate error; and correcting the first mechanical drilling speed through the drilling speed error to obtain a second mechanical drilling speed.
The determining unit 830 is configured to take, as the optimal drilling parameter value, a parameter value of each controllable parameter in a set of parameter values corresponding to the maximum value of the second mechanical drilling speed.
In some embodiments, the third obtaining unit 810 includes an obtaining subunit 811 for obtaining a plurality of hydraulic parameters of the target work area and a value range of each hydraulic parameter, where the hydraulic parameters include at least one of: drilling fluid density, apparent viscosity of drilling fluid, diameter of drill bit nozzle, flow rate of injected drilling fluid.
In some embodiments, the generating unit 820 and the determining unit 830 include a setting subunit 8231, a generating subunit 8232, a calculating subunit 8233, a determining subunit 8234, and an adjusting subunit 8235.
The setting subunit 8231 is configured to set a predetermined number of variables.
The generating subunit 8232 is configured to generate a predetermined number of sets of parameter values according to the value ranges of the controllable parameters, where each set of parameter values includes parameter values of the plurality of controllable parameters.
The calculating subunit 8233 is configured to assign a set of parameter values to each variable, and calculate a second rate of penetration corresponding to the set of parameter values to which each variable is assigned.
The determining subunit 8234 is configured to take a variable corresponding to the maximum value of the second mechanical drilling speed as an optimal variable.
The adjustment subunit 8235 is configured to adjust each variable according to the current optimal variable and a predetermined adjustment amplitude of each controllable parameter according to the following method: carrying out multiple times of adjustment on the variable to obtain a plurality of groups of parameter values, wherein each time of adjustment is based on a group of parameter values currently corresponding to the variable, and adjusting the parameter value of at least one controllable parameter in the group of parameter values currently corresponding to the variable; and calculating the second mechanical drilling speed corresponding to each set of parameter values obtained through adjustment, and taking the set of parameter values corresponding to the maximum mechanical drilling speed as the set of parameter values corresponding to the adjusted variables.
The calculating subunit 8233 is further configured to calculate a second rate of penetration corresponding to a set of parameter values corresponding to each of the adjusted variables.
The determining subunit 8234 is further configured to take, as an optimal variable, an adjusted variable corresponding to the second rate of penetration that is the maximum value.
The adjusting subunit 8235, the calculating subunit 8233 and the determining subunit 8234 execute the loop until the preset loop termination condition is reached, and the determining subunit 8234 takes the parameter value of each controllable parameter in a group of parameter values corresponding to the optimal variable as the optimal drilling parameter.
The details of the above-mentioned device for determining the rate of penetration may be understood by referring to the description and effects related to the corresponding embodiment of fig. 4, and will not be repeated here.
The present invention also provides an electronic device, as shown in fig. 9, which may include a processor 901 and a memory 902, where the processor 901 and the memory 902 may be connected by a bus or other means, and in fig. 9, the connection is exemplified by a bus.
The processor 901 may be a central processing unit (Central Processing Unit, CPU). The processor 901 may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination thereof.
The memory 902 is used as a non-transitory computer readable storage medium, and may be used to store a non-transitory software program, a non-transitory computer executable program, and a module, such as program instructions/modules corresponding to the method for determining a rate of penetration or the method for optimizing drilling parameters in the embodiment of the present invention (e.g., the first obtaining unit 710, the first calculating unit 720, the predicting unit 730, and the modifying unit 740 shown in fig. 7, or the third obtaining unit 810, the generating unit 820, and the determining unit 830 shown in fig. 8). The processor 901 executes various functional applications of the processor and data classification, i.e., implements the rate of penetration determination method or the drilling parameter optimization method in the above-described method embodiments, by running non-transitory software programs, instructions, and modules stored in the memory 902.
The memory 902 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, at least one application program required for a function; the storage data area may store data created by the processor 901, and the like. In addition, the memory 902 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, memory 902 optionally includes memory remotely located relative to processor 901, which may be connected to processor 901 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The one or more modules are stored in the memory 902 and when executed by the processor 901 perform the rate of penetration determination method or the drilling parameter optimization method of the embodiments shown in fig. 1 or 4.
The details of the above electronic device may be understood by referring to the related descriptions and effects in the corresponding embodiment of fig. 1 or fig. 4, which are not repeated here.
It will be appreciated by those skilled in the art that the modules or steps of the application described above may be implemented in a general purpose computing device, they may be concentrated on a single computing device, or distributed across a network of computing devices, they may alternatively be implemented in program code executable by computing devices, so that they may be stored in a memory device for execution by computing devices, and in some cases, the steps shown or described may be performed in a different order than that shown or described, or they may be separately fabricated into individual integrated circuit modules, or multiple modules or steps within them may be fabricated into a single integrated circuit module for implementation. Thus, the present application is not limited to any specific combination of hardware and software.
The above description is only of the preferred embodiments of the present application and is not intended to limit the present application, but various modifications and variations can be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims (9)

1. A method of determining a rate of penetration comprising:
acquiring parameter values of a plurality of drilling parameters in a target work area;
substituting the parameter values of the drilling parameters into a mechanical drilling speed equation, and calculating to obtain a first mechanical drilling speed;
substituting the parameter values of the drilling parameters into a preset prediction model, and predicting to obtain a drilling rate error; the prediction model is an artificial intelligent network model;
correcting the first mechanical drilling speed through the drilling speed error to obtain a second mechanical drilling speed, and taking the second mechanical drilling speed as a target mechanical drilling speed;
substituting the values of the drilling parameters into a preset prediction model, and before predicting to obtain the drilling rate error, further comprising:
obtaining a plurality of groups of sample parameter values of a plurality of drilling parameters of a target work area, wherein each group of sample parameter values comprises a mechanical drilling speed sample value and sample values of corresponding drilling parameters;
for each set of sample parameter values, the following operations are performed to train the predictive model: substituting the sample values of all drilling parameters in the current set of sample parameter values into the mechanical drilling speed equation, and calculating to obtain a first mechanical drilling speed; calculating a difference between the sample value of the rate of penetration and the first rate of penetration as a rate of penetration error; and training the prediction model by taking the drilling speed error as the output of the prediction model and taking the sample value of each drilling parameter in the current set of sample parameter values as the input of the prediction model.
2. The method of claim 1, wherein the rate of penetration equation is:
wherein ROP represents the rate of penetration;
coefficient a 1 Representing the effect of formation strength on the rate of penetration;
coefficient a 2 Indicating the effect of formation compaction on the rate of penetration, D indicating the drilling depth;
coefficient a 3 Indicating the effect of formation undercompacting on the rate of penetration, TVD indicating the sag, g p Representing formation pressure, ECD represents the density of the circulating drilling fluid;
coefficient a 4 Representing the effect of the bottom hole differential pressure on the mechanical drilling speed;
coefficient a 5 Representing the effect of weight on the rate of penetration, W representing weight on bit, D b Indicating the diameter of the drill bit, t is a subscript, ++>Representing the ratio of minimum weight on bit to bit diameter required to break rock;
coefficient a 6 The influence of the rotation speed on the mechanical drilling speed is shown, and N is the rotation speed;
coefficient a 7 Indicating the influence of drill bit abrasion on the mechanical drilling speed, wherein h indicates the drill bit abrasion amount;
coefficient a 8 The effect of bit hydraulics on the rate of penetration is expressed, ρ is the density of the drilling fluid, q is the flow rate of the drilling fluid injected, μ is the apparent viscosity of the drilling fluid, d n Indicating the drill bit nozzle diameter.
3. A method of optimizing drilling parameters, comprising:
acquiring a plurality of controllable parameters of a target work area and a value range of the controllable parameters;
Generating a plurality of groups of parameter values according to the value range of each controllable parameter, and respectively calculating a second mechanical drilling speed corresponding to each group of parameter values; wherein, each group of parameter values comprises parameter values of the controllable parameters, and the second mechanical drilling speed corresponding to one group of parameter values is obtained according to the following method: substituting the parameter values of each controllable parameter in the set of parameter values into a mechanical drilling speed equation, and calculating to obtain a first mechanical drilling speed; substituting the parameter values of each controllable parameter in the group of parameter values into a preset prediction model, and predicting to obtain a drilling rate error; correcting the first mechanical drilling speed through the drilling speed error to obtain a second mechanical drilling speed; the prediction model is an artificial intelligent network model;
taking the parameter value of each controllable parameter in a group of parameter values corresponding to the maximum value of the second mechanical drilling speed as an optimal drilling parameter value;
the artificial intelligent network model is obtained through training by the following method:
obtaining a plurality of groups of sample parameter values of a plurality of drilling parameters of a target work area, wherein each group of sample parameter values comprises a mechanical drilling speed sample value and sample values of corresponding drilling parameters;
for each set of sample parameter values, the following is performed: substituting the sample values of all drilling parameters in the current set of sample parameter values into the mechanical drilling speed equation, and calculating to obtain a first mechanical drilling speed; calculating a difference between the sample value of the rate of penetration and the first rate of penetration as a rate of penetration error; and training the prediction model by taking the drilling speed error as the output of the prediction model and taking the sample value of each drilling parameter in the current set of sample parameter values as the input of the prediction model.
4. A method according to claim 3, wherein obtaining a plurality of controllable parameters of the target work area and a range of values for each controllable parameter comprises:
acquiring a plurality of hydraulic parameters of a target work area and a value range of each hydraulic parameter, wherein the hydraulic parameters comprise at least one of the following: drilling fluid density, apparent viscosity of drilling fluid, diameter of drill bit nozzle, flow rate of injected drilling fluid.
5. A method according to claim 3, wherein a plurality of sets of parameter values are generated according to the value ranges of the controllable parameters, and the second rate of penetration corresponding to each set of parameter values is calculated; taking the parameter value of each controllable parameter in a group of parameter values corresponding to the maximum value of the second mechanical drilling speed as the optimal drilling parameter value, wherein the method comprises the following steps:
setting a predetermined number of variables;
generating a preset number of groups of parameter values according to the value range of each controllable parameter, wherein each group of parameter values comprises parameter values of the plurality of controllable parameters;
assigning a set of parameter values to each variable, and calculating a second rate of penetration corresponding to the assigned set of parameter values for each variable;
taking a variable corresponding to the maximum value of the second mechanical drilling speed as an optimal variable;
The following steps are circularly executed until a preset cycle termination condition is reached, and the parameter value of each controllable parameter in a group of parameter values corresponding to the optimal variable is used as the optimal drilling parameter:
according to the current optimal variable and the preset adjustment amplitude of each controllable parameter, each variable is adjusted according to the following method: carrying out multiple times of adjustment on the variable to obtain a plurality of groups of parameter values, wherein each time of adjustment is based on a group of parameter values currently corresponding to the variable, and adjusting the parameter value of at least one controllable parameter in the group of parameter values currently corresponding to the variable; calculating the second mechanical drilling speed corresponding to each set of parameter values obtained through adjustment, and taking a set of parameter values corresponding to the maximum value of the second mechanical drilling speed as a set of parameter values corresponding to the adjusted variables;
calculating a second mechanical drilling rate corresponding to a group of parameter values corresponding to each adjusted variable;
and taking the adjusted variable corresponding to the maximum value of the second mechanical drilling speed as an optimal variable.
6. A rate of penetration determination apparatus, comprising:
the first acquisition unit is used for acquiring parameter values of a plurality of drilling parameters in the target work area;
the first calculation unit is used for substituting the parameter values of the drilling parameters into a mechanical drilling speed equation to calculate and obtain a first mechanical drilling speed;
The prediction unit is used for substituting the parameter values of the drilling parameters into a preset prediction model to predict and obtain drilling speed errors; the prediction model is an artificial intelligent network model;
the correction unit is used for correcting the first mechanical drilling speed through the drilling speed error to obtain a second mechanical drilling speed, and taking the second mechanical drilling speed as a target mechanical drilling speed;
the artificial intelligent network model is obtained through training by the following method:
obtaining a plurality of groups of sample parameter values of a plurality of drilling parameters of a target work area, wherein each group of sample parameter values comprises a mechanical drilling speed sample value and sample values of corresponding drilling parameters;
for each set of sample parameter values, the following is performed: substituting the sample values of all drilling parameters in the current set of sample parameter values into the mechanical drilling speed equation, and calculating to obtain a first mechanical drilling speed; calculating a difference between the sample value of the rate of penetration and the first rate of penetration as a rate of penetration error; and training the prediction model by taking the drilling speed error as the output of the prediction model and taking the sample value of each drilling parameter in the current set of sample parameter values as the input of the prediction model.
7. A drilling parameter optimization apparatus, comprising:
the third acquisition unit is used for acquiring a plurality of controllable parameters and the value ranges of the controllable parameters of the target work area;
the generating unit is used for generating a plurality of groups of parameter values according to the value range of each controllable parameter, and respectively calculating a second mechanical drilling speed corresponding to each group of parameter values; wherein, each group of parameter values comprises parameter values of the controllable parameters, and the second mechanical drilling speed corresponding to one group of parameter values is obtained according to the following method: substituting the parameter values of each controllable parameter in the set of parameter values into a mechanical drilling speed equation, and calculating to obtain a first mechanical drilling speed; substituting the parameter values of each controllable parameter in the group of parameter values into a preset prediction model, and predicting to obtain a drilling rate error; correcting the first mechanical drilling speed through the drilling speed error to obtain a second mechanical drilling speed; the prediction model is an artificial intelligent network model;
the determining unit is used for taking the parameter value of each controllable parameter in a group of parameter values corresponding to the maximum value of the second mechanical drilling speed as an optimal drilling parameter value;
the artificial intelligent network model is obtained through training by the following method:
obtaining a plurality of groups of sample parameter values of a plurality of drilling parameters of a target work area, wherein each group of sample parameter values comprises a mechanical drilling speed sample value and sample values of corresponding drilling parameters;
For each set of sample parameter values, the following is performed: substituting the sample values of all drilling parameters in the current set of sample parameter values into the mechanical drilling speed equation, and calculating to obtain a first mechanical drilling speed; calculating a difference between the sample value of the rate of penetration and the first rate of penetration as a rate of penetration error; and training the prediction model by taking the drilling speed error as the output of the prediction model and taking the sample value of each drilling parameter in the current set of sample parameter values as the input of the prediction model.
8. An electronic device, comprising:
a memory and a processor in communication with each other, the memory having stored therein computer instructions which, upon execution, cause the processor to perform the steps of the method of any of claims 1 to 5.
9. A computer storage medium storing computer program instructions which, when executed, implement the steps of the method of any one of claims 1 to 5.
CN202210025176.7A 2022-01-11 2022-01-11 Mechanical drilling speed determination and drilling parameter optimization method and device and electronic equipment Active CN114370264B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210025176.7A CN114370264B (en) 2022-01-11 2022-01-11 Mechanical drilling speed determination and drilling parameter optimization method and device and electronic equipment

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210025176.7A CN114370264B (en) 2022-01-11 2022-01-11 Mechanical drilling speed determination and drilling parameter optimization method and device and electronic equipment

Publications (2)

Publication Number Publication Date
CN114370264A CN114370264A (en) 2022-04-19
CN114370264B true CN114370264B (en) 2023-12-15

Family

ID=81143446

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210025176.7A Active CN114370264B (en) 2022-01-11 2022-01-11 Mechanical drilling speed determination and drilling parameter optimization method and device and electronic equipment

Country Status (1)

Country Link
CN (1) CN114370264B (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114856540B (en) * 2022-05-11 2024-05-28 西南石油大学 Horizontal well mechanical drilling speed while drilling prediction method based on online learning
CN117703344B (en) * 2024-02-01 2024-04-30 成都三一能源环保技术有限公司 Drilling parameter adjusting method based on data analysis

Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4407017A (en) * 1978-09-06 1983-09-27 Zhilikov Valentin V Method and apparatus for controlling drilling process
CN103177185A (en) * 2013-03-13 2013-06-26 中国石油大学(北京) Method and device for polycrystalline diamond compact bit (PDC) drilling parameter multi-objective optimization
CN105952377A (en) * 2016-05-03 2016-09-21 中煤科工集团西安研究院有限公司 Method for controlling path of coal mine underground directional drilling
CN107038307A (en) * 2017-04-18 2017-08-11 中南大学 Mechanism predicts integrated modelling approach with the Roller Conveying Kiln for Temperature that data are combined
CN107193055A (en) * 2017-05-27 2017-09-22 中国地质大学（武汉） A kind of complicated geological drilling process Double-layer intelligent drilling speed modeling
CN110857626A (en) * 2018-08-14 2020-03-03 中国石油天然气股份有限公司 While-drilling pressure prediction method and device based on comprehensive logging parameters and storage medium
CN112069646A (en) * 2020-07-17 2020-12-11 中国石油化工股份有限公司 Method for accurately predicting mechanical drilling speed
CN112487582A (en) * 2020-12-10 2021-03-12 西南石油大学 Oil-gas drilling machinery drilling speed prediction and optimization method based on CART algorithm
CN112861438A (en) * 2021-02-22 2021-05-28 中国石油化工股份有限公司石油工程技术研究院 Drilling machine drilling speed prediction method based on theoretical model and data fusion
CN112901137A (en) * 2021-03-08 2021-06-04 西南石油大学 Deep well drilling mechanical drilling speed prediction method based on deep neural network Sequential model
CN113689055A (en) * 2021-10-22 2021-11-23 西南石油大学 Oil-gas drilling machinery drilling speed prediction and optimization method based on Bayesian optimization

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10125558B2 (en) * 2014-05-13 2018-11-13 Schlumberger Technology Corporation Pumps-off annular pressure while drilling system

Patent Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4407017A (en) * 1978-09-06 1983-09-27 Zhilikov Valentin V Method and apparatus for controlling drilling process
CN103177185A (en) * 2013-03-13 2013-06-26 中国石油大学(北京) Method and device for polycrystalline diamond compact bit (PDC) drilling parameter multi-objective optimization
CN105952377A (en) * 2016-05-03 2016-09-21 中煤科工集团西安研究院有限公司 Method for controlling path of coal mine underground directional drilling
CN107038307A (en) * 2017-04-18 2017-08-11 中南大学 Mechanism predicts integrated modelling approach with the Roller Conveying Kiln for Temperature that data are combined
CN107193055A (en) * 2017-05-27 2017-09-22 中国地质大学（武汉） A kind of complicated geological drilling process Double-layer intelligent drilling speed modeling
CN110857626A (en) * 2018-08-14 2020-03-03 中国石油天然气股份有限公司 While-drilling pressure prediction method and device based on comprehensive logging parameters and storage medium
CN112069646A (en) * 2020-07-17 2020-12-11 中国石油化工股份有限公司 Method for accurately predicting mechanical drilling speed
CN112487582A (en) * 2020-12-10 2021-03-12 西南石油大学 Oil-gas drilling machinery drilling speed prediction and optimization method based on CART algorithm
CN112861438A (en) * 2021-02-22 2021-05-28 中国石油化工股份有限公司石油工程技术研究院 Drilling machine drilling speed prediction method based on theoretical model and data fusion
CN112901137A (en) * 2021-03-08 2021-06-04 西南石油大学 Deep well drilling mechanical drilling speed prediction method based on deep neural network Sequential model
CN113689055A (en) * 2021-10-22 2021-11-23 西南石油大学 Oil-gas drilling machinery drilling speed prediction and optimization method based on Bayesian optimization

Non-Patent Citations (7)

* Cited by examiner, † Cited by third party
Title
Machine learning methods applied to drilling rate of penetration prediction and optimization - A review;Luís Felipe F.M. Barbosa,etc;Journal of Petroleum Science and Engineering;第1-20页 *
PDC钻头钻速方程影响因素综述;魏凯等;内蒙古石油化工;第63-65页 *
Prediction of Penetration Rate for PDC Bits Using Indices of Rock Drillability, Cuttings Removal, and Bit Wear;Ahmed Z. Mazen，etc;SPE Drilling & Completion;第1-18页 *
Real-time optimization of drilling parameters based on mechanical specific energy for rotating drilling with positive displacement motor in the hard formation;Xuyue Chen,etc;Journal of Natural Gas Science and Engineering;第686-694页 *
Real-time prediction of rate of penetration while drilling complex lithologies using artificial intelligence techniques;Salaheldin Elkatatny;Ain Shams Engineering Journal;第917-926页 *
基于多元回归分析的钻速预测方法研究;李昌盛;科学技术与工程;第13卷(第7期);第1740-1744页 *
河南油田钻进参数的优化研究;周劲辉等;探矿工程（岩土钻掘工程）;第270-272页 *

Also Published As

Publication number Publication date
CN114370264A (en) 2022-04-19

Similar Documents

Publication Publication Date Title
CN114370264B (en) Mechanical drilling speed determination and drilling parameter optimization method and device and electronic equipment
US10801314B2 (en) Real-time trajectory control during drilling operations
US10221671B1 (en) MSE based drilling optimization using neural network simulaton
US11598195B2 (en) Statistical approach to incorporate uncertainties of parameters in simulation results and stability analysis for earth drilling
CA3093668C (en) Learning based bayesian optimization for optimizing controllable drilling parameters
KR102294384B1 (en) Method for constructing drilling driving guide model to predict drilling rate using machine learning and system for predicting drilling rate using thereof
GB2600589A (en) Method of modeling fluid flow downhole and related apparatus and systems
CN104145079A (en) Determining optimal parameters for a downhole operation
US20190234207A1 (en) Optimization of rate-of-penetration
CN113689055A (en) Oil-gas drilling machinery drilling speed prediction and optimization method based on Bayesian optimization
CN115329657B (en) Drilling parameter optimization method and device
US11448057B2 (en) Adjusting well tool operation to manipulate the rate-of-penetration (ROP) of a drill bit based on multiple ROP projections
US20220137568A1 (en) Predictive models and multi-objective constraint optimization algorithm to optimize drilling parameters of a wellbore
CN109973072A (en) A kind of frictional resistance prediction technique and device
US11639657B2 (en) Controlling wellbore equipment using a hybrid deep generative physics neural network
Yamaliev et al. About the deep drilling equipment technical condition recognition method
US12044117B2 (en) Methods for estimating downhole weight on bit and rate of penetration using acceleration measurements
Hamdi et al. Improving drilling rate of penetration modelling performance using adaptive neuro-fuzzy inference systems
Mnati et al. Prediction of penetration rate and cost with artificial neural network for alhafaya oil field
Duan et al. A ROP prediction approach based on improved BP neural network
CN117287179B (en) Remote control system and method for precision drilling and production equipment
US20220187494A1 (en) Decomposed friction factor calibration
CN117057661A (en) Processing method and equipment
CN117231196A (en) Determination method and device for full-well-section high-resolution logging data
CN116006168A (en) Injection and production parameter optimization method and system based on connectivity analysis

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant