WO2016179767A1

WO2016179767A1 - Fatigue analysis procedure for drill string

Info

Publication number: WO2016179767A1
Application number: PCT/CN2015/078623
Authority: WO
Inventors: Sujian Huang
Original assignee: Schlumberger Technology Corporation; Schlumberger Canada Limited; Services Petroliers Schlumberger; Geoquest Systems B. V.
Priority date: 2015-05-08
Filing date: 2015-05-08
Publication date: 2016-11-17

Abstract

A method, system, and computer readable medium for management of fatigue life are disclosed. Management of fatigue life includes partitioning a drill string into sections, calculating a stress value for each section. From the stress value, an equivalent stress amplitude is calculated for each section, and a fatigue life consumption is calculated for each section, and a fatigue life consumption value in each section is computed. The fatigue life consumption value across the sections is aggregated to obtain an aggregated fatigue life consumption value.

Description

FATIGUE ANALYSIS PROCEDURE FOR DRILL STRING

BACKGROUND

Computer simulation estimates the operations of a real-world system. Generally, computer simulation allows a user to test various control parameters to select an optimal control parameter. For example, in field management, computer simulation may be used to plan the drilling and production of valuable downhole assets. In particular, drilling simulation is used extensively to design drilling tools and plan for drilling operations.

SUMMARY

In general, in one aspect, embodiments relate to a method, system, and computer readable medium for management of fatigue life. Management of fatigue life includes partitioning a drill string into sections, calculating a stress value for each section. From the stress value, an equivalent stress amplitude is calculated for each section, and a fatigue life consumption value in each section is computed. The fatigue life consumption value across the sections is aggregated to obtain an aggregated fatigue life consumption value, which is presented.

Other aspects of the technology will be apparent from the following description and the appended claims.

BRIEF DESCRIPTION OF DRAWINGS

FIGs. 1, 2, 3, and 4 show schematic diagrams in accordance with one or more embodiments of the technology.

FIGs. 5.1, 5.2, 6, 8, and 9 show examples in accordance with one or more embodiments of the technology.

FIG. 7 shows a flowchart in accordance with one or more embodiments of the technology.

DETAILED DESCRIPTION

Specific embodiments of the technology will now be described in detail with reference to the accompanying figures. Like elements in the various figures are denoted by like reference numerals for consistency.

In the following detailed description of embodiments of the technology, numerous specific details are set forth in order to provide a more thorough understanding of the technology. However, it will be apparent to one of ordinary skill in the art that the technology may be practiced without these specific details. In other instances, well-known features have not been described in detail to avoid unnecessarily complicating the description.

Throughout the application, ordinal numbers (e. g. , first, second, third, etc. ) may be used as an adjective for an element (i.e., any noun in the application) . The use of ordinal numbers is not to imply or create any particular ordering of the elements nor to limit any element to being a single element unless expressly disclosed, such as by the use of the terms "before" , "after" , "single" , and other such terminology. Rather, the use of ordinal numbers is to distinguish between the elements. By way of an example, a first element is distinct from a second element, and the first element may encompass more than one element and succeed (or precede) the second element in an ordering of elements.

In general, embodiments of the technology are directed to real-time management of drilling operations. In particular, a drilling model is calibrated. Simulations are continually performed on using the calibrated drilling model. A predicted measurement value from the simulations is compared against an actual measurement value acquired from the field. If the actual measurement value matches the simulated measurement value, then the simulations may be used to determine a simulated state of the drilling operation. Based on the simulated state, a condition of the drilling operation is determined and a notification of the condition presented.

One or more embodiments are directed to a drilling simulation-based real time system for drilling operation monitoring, diagnostics and optimization. In particular, one or more embodiments may perform diagnostics and optimization for drilling. For example, one or more embodiments may perform real-time vibration mitigation, real-time rate of penetration (ROP) optimization, real-time trajectory monitoring and directional drilling recommendation, real-time wellbore quality optimization, real-time logging while drilling/measurement while drilling (LWD/WMD) measurement quality assurance, real-time fatigue life monitoring, real-time bit-reamer load balancing, real-time bit and reamer wear monitoring, and real-time buckling and weight on bit (WOB) transfer monitoring.

Trajectory monitoring may include ensuring that trajectory is within a threshold of the desired planned direction. Wellbore quality is the degree of straightness of the hole. Fatigue life managing is managing stress on equipment, such as when rotating while drilling the hole. One or more embodiments may detect and manage the remaining amount of life of each part of equipment. Bit reamer load balancing is managing an amount the reamer expands as compared to the amount that the bit cuts. Bit and reamer wear monitoring may include detecting and managing when the cutters go blunt. Buckling and weight on bit transfer monitoring may include managing when cutters go blunt, and preventing or managing deformation of the drill pipes.

FIG. 1 depicts a schematic view, partially in cross section, of a field (100) in which one or more embodiments may be implemented. In one or more embodiments, the field may be an oilfield. In other embodiments, the field may be a different type of field. In one or more embodiments, one or more of the modules and elements shown in FIG. 1 may be omitted, repeated, and/or substituted. Accordingly, embodiments should not be considered limited to the specific arrangements of modules shown in FIG. 1.

A subterranean formation (104) is in an underground geological region. An underground geological region is a geographic area that exists below land or ocean. In one or more embodiments, the underground geological region includes the subsurface formation in which a borehole is or may be drilled and any subsurface region that may affect the drilling of the borehole, such as because of stresses and strains existing in the subsurface region. In other words, the underground geological region may not just include the area immediately surrounding a borehole or where a borehole may be drilled, but also any area that affects or may affect the borehole or where the borehole may be drilled.

As shown in FIG. 1, the subterranean formation (104) may include several geological structures (106-1 through 106-4) of which FIG. 1 provides an example. As shown, the formation may include a sandstone layer (106-1) , a limestone layer (106-2) , a shale layer (106-3) , and a sand layer (106-4) . A fault line (107) may extend through the formation. In one or more embodiments, various survey tools and/or data acquisition tools are adapted to measure the formation and detect the characteristics of the geological structures of the formation. Further, as shown in FIG. 1, the wellsite system (110) is associated with a rig (101) , a wellbore (103) , and other field equipment and is configured to perform wellbore operations, such as logging, drilling, fracturing, production, or other applicable operations. The wellbore (103) may also be referred to as a borehole.

In one or more embodiments, the surface unit (112) is operatively coupled to a field management tool (116) and/or the wellsite system (110) . In particular, the surface unit (112) is configured to communicate with the field management tool (116) and/or the wellsite system (110) to send commands to the field management tool (116) and/or the wellsite system (110) and to receive data therefrom. For example, the wellsite system (110) may be adapted for measuring downhole properties using logging-while-drilling ( “LWD” ) tools to obtain well logs and for obtaining core samples. In one or more embodiments, the surface unit (112) may be located at the wellsite system (110) and/or remote locations. The surface unit (112) may be provided with computer facilities for receiving, storing, processing, and/or analyzing data from the field management tool (116) , the wellsite system (110) , or other part of the field (100) . The surface unit (112) may also be provided with or functionally for actuating mechanisms at the field (100) . The surface unit (112) may then send command signals to the field (100) in response to data received, for example, to control and/or optimize various field operations described above.

During the various oilfield operations at the field, data is collected for analysis and/or monitoring of the oilfield operations. Such data may include, for example, subterranean formation, equipment, historical and/or other data. Static data relates to, for example, formation structure and geological stratigraphy that define the geological structures of the subterranean formation. Static data may also include data about the wellbore, such as inside diameters, outside diameters, and depths. Dynamic data relates to, for example, fluids flowing through the geologic structures of the subterranean formation over time. The dynamic data may include, for example, pressures, fluid compositions (e.g. gas oil ratio, water cut, and/or other fluid compositional information) , and states of various equipment, and other information.

The static and dynamic data collected from the wellbore and the oilfield may be used to create and update a three dimensional model of the subsurface formations. Additionally, static and dynamic data from other wellbores or oilfields may be used to create and update the three dimensional model. Hardware sensors, core sampling, and well logging techniques may be used to collect the data. Other static measurements may be gathered using downhole measurements, such as core sampling and well logging techniques. Well logging involves deployment of a downhole tool into the wellbore to collect various downhole measurements, such as density, resistivity, etc., at various depths. Such well logging may be performed using, for example, a drilling tool and/or a wireline tool, or sensors located on downhole production equipment. Once the well is formed and completed, fluid flows to the surface using production tubing and other completion equipment. As fluid passes to the surface, various dynamic measurements, such as fluid flow rates, pressure, and composition may be monitored. These parameters may be used to determine various characteristics of the subterranean formation.

In one or more embodiments, the data is received by the surface unit (112) , which is communicatively coupled to the field management tool (116) . Generally, the field management tool (116) is configured to analyze, model, control, optimize, or perform other management tasks of the aforementioned field operations based on the data provided from the surface unit (112) . Although the surface unit (112) is shown as separate from the field management tool (116) in FIG. 1, in other examples, the surface unit (112) and the field management tool (116) may also be combined.

During a drilling operation, drilling tools are deployed from the oil and gas rigs. The drilling tools advanced into the earth along a path to locate reservoirs containing the valuable downhole assets. In one or more embodiments, the optimal path for the drilling is identified in a well plan that uses three-dimensional modeling.

Fluid, such as drilling mud or other drilling fluids, is pumped down the wellbore (or borehole) through the drilling tool and out the drilling bit. The drilling fluid flows through the annulus between the drilling tool and the wellbore and out the surface, carrying away earth loosened during drilling. The drilling fluids return the earth to the surface, and seal the wall of the wellbore to prevent fluid in the surrounding earth from entering the wellbore and causing a ‘blow out’ .

During the drilling operation, the drilling tool may perform downhole measurements to investigate downhole conditions. The drilling tool may be used to take core samples of subsurface formations. In some cases, the drilling tool is removed and a wireline tool is deployed into the wellbore to perform additional downhole testing, such as logging or sampling. Steel casing may be run into the well to a desired depth and cemented into place along the wellbore wall. Drilling may be continued until the desired total depth is reached.

After the drilling operation is complete, the well may then be prepared for production. Wellbore completions equipment is deployed into the wellbore to complete the well in preparation for the production of fluid through the wellbore. Fluid is then allowed to flow from downhole reservoirs, into the wellbore and to the surface. Production facilities are positioned at surface locations to collect the hydrocarbons from the wellsite (s) . Fluid drawn from the subterranean reservoir (s) passes to the production facilities via transport mechanisms, such as tubing. Various equipment may be positioned about the oilfield to monitor oilfield parameters, to manipulate the oilfield operations and/or to separate and direct fluids from the wells. Surface equipment and completion equipment may also be used to inject fluids into reservoir either for storage or at strategic points to enhance production of the reservoir.

Sensors (S) are located about the wellsite to collect data, may be in real time, concerning the operation of the wellsite, as well as conditions at the wellsite. The sensors may also have features or capabilities, of monitors, such as cameras (not shown) , to provide pictures of the operation. Surface sensors or gauges S may be deployed about the surface systems to provide information about the surface unit, such as standpipe pressure, hook load, depth, surface torque, rotary rpm, among others. Downhole sensors or gauges (S) are disposed about the drilling tool and/or wellbore to provide information about downhole conditions, such as wellbore pressure, weight on bit, torque on bit, direction, inclination, collar rpm, tool temperature, annular temperature, and tool face, among others. For example, the sensors may include one or more of a camera, a pressure sensor, a temperature sensor, a flow rate sensor, a vibration sensor, a current sensor, a voltage sensor, a resistance sensor, a gesture detection sensor or device, a voice actuated or recognition device or sensor, or other suitable sensors. Example down hole drill string sensors include functionality to obtain drilling dynamics measurements, such as tri-axis accelerations, collar rotations per minute (RPM) and stick-slip, bending moment, down hole torque, and axial weight. Sensors that perform measurement while drilling and logging while drilling may include functionality to perform caliper logging, acquire annulus pressure and equivalent circulating density (ECD) measurements, perform a well survey, acquire shock and vibration measurements, and obtain formation information at the drilling depths and ahead of bit. The information collected by the sensors and cameras is conveyed to the various parts of the drilling system and/or the surface control unit.

At the rig floor or the surface, the sensors may include functionality to obtain input drilling parameters (e.g., Source RPM (SRPM) (actual table revolution) , rotating/sliding, rotary steerable system (RSS) steering ratio and through flow line (TF) , weight on bit (WOB) and hook load, and flow rate and MW) , surface drilling measurements (e.g., surface torque, stand pipe pressure, top drive block location/feeding speed (ROP) ) , and mud logging (e.g., cuttings, and formation type and unconfined compression strength (UCS) ) .

FIG. 2 shows a schematic diagram depicting drilling operation of a directional well in multiple sections. The drilling operation depicted in FIG. 2 includes a wellsite drilling system (200) and a field management tool (220) for accessing fluid in the target reservoir through a bore hole (250) of a directional well (217) . The wellsite drilling system (200) includes various components (e.g., drill string (212) , annulus (212) , bottom hole assembly (BHA) (214) , Kelly (215) , mud pit (216) , etc. ) as generally described with respect to the wellsite drilling systems (100) (e.g., drill string (115) , annulus (126) , bottom hole assembly (BHA) (120) , Kelly (116) , mud pit (122) , etc. ) of FIG. 1 above. As shown in FIG. 2, the target reservoir may be located away from (as opposed to directly under) the surface location of the well (217) . Accordingly, special tools or techniques may be used to ensure that the path along the bore hole (250) reaches the particular location of the target reservoir (200) .

For example, the BHA (214) may include sensors (208) , rotary steerable system (209) , and the bit (210) to direct the drilling toward the target guided by a pre-determined survey program for measuring location details in the well. Furthermore, the subterranean formation through which the directional well (217) is drilled may include multiple layers (not shown) with varying compositions, geophysical characteristics, and geological conditions. Both the drilling planning during the well design stage and the actual drilling according to the drilling plan in the drilling stage may be performed in multiple sections (e.g., sections (201) , (202) , (202) , (204) ) corresponding to the multiple layers in the subterranean formation. For example, certain sections (e.g., sections (201) and (202) ) may use cement (207) reinforced casing (206) due to the particular formation compositions, geophysical characteristics, and geological conditions.

Further as shown in FIG. 2, surface unit (211) (as generally described with respect to the surface unit (124) of FIG. 1) may be operatively linked to the wellsite drilling system (200) and the field management tool (220) via communication links (218) . The surface unit (211) may be configured with functionalities to control and monitor the drilling activities by sections in real-time via the communication links (218) . The field management tool (220) may be configured with functionalities to store oilfield data (e.g., historical data, actual data, surface data, subsurface data, equipment data, geological data, geophysical data, target data, anti-target data, etc. ) and determine relevant factors for configuring a drilling model and generating a drilling plan. The oilfield data, the drilling model, and the drilling plan may be transmitted via the communication link (218) according to a drilling operation workflow. The communication link (218) may comprise the communication subassembly (252) as described with respect to FIG. 1 above.

To facilitate the processing and analysis of data, simulators may be used to process the data. Specific simulators are often used in connection with specific oilfield operations, such as reservoir or wellbore production. Data fed into the simulator (s) may be historical data, real time data or combinations thereof. Simulation through one or more of the simulators may be repeated or adjusted based on the data received.

The oilfield operation is provided with wellsite and non-wellsite simulators. The wellsite simulators may include a reservoir simulator, a wellbore simulator, and a surface network simulator. The reservoir simulator solves for hydrocarbon flowrate through the reservoir and into the wellbores. The wellbore simulator and surface network simulator solve for hydrocarbon flowrate through the wellbore and the surface gathering network of pipelines. As shown, some of the simulators may be separate or combined, depending on the available systems.

The non-wellsite simulators may include process and economics simulators. The processing unit has a process simulator. The process simulator models the processing plant (e.g., the process facility) where the hydrocarbon is separated into its constituent components (e.g., methane, ethane, propane, etc. ) and prepared for sales. The oilfield is provided with an economics simulator. The economics simulator models the costs of part or the entire oilfield. Various combinations of these and other oilfield simulators may be provided.

FIG. 3 shows an example of a communication structure in accordance with one or more embodiments of the technology. As shown in FIG. 3, downhole sensors (300) may transmit data (302) via the communication link to a surface unit (304) . Similarly, rig surface data (306) may also be transmitted to surface unit (304) . The surface unit may provide the data to a simulation server (308) . For example, the simulation server (308) may execute the field management tool, discussed above.

As shown in FIG. 3, real time information is obtained from the wellsite as part of data acquisition and monitoring. Further, wellbore and reservoir information may be gathered. The surface unit may compile the gathered information and send the information to the simulation server. For example, the surface unit may interface with the controller for each item of equipment to gather and compile the information. When gathering the information, sensors might not be located along the entire length of the drill string, but rather a few positions may have measurement values. In such a scenario, when the simulator receives the gathered information, the simulator may provide an estimation as to the remaining positions. The simulator may include functionality to generate dynamics simulation model, calibrate and re-calibrate the model using real-time data, execute the calibrated model, monitor variables through simulation, identify and warn of dangerous conditions, and explore parameters to mitigate adverse drilling dynamics. The simulator may provide simulation results to the surface unit, which displays the simulation results and event warnings.

Variables monitoring and diagnostics may include monitoring drilling efficiency (e.g., cutting structure compatibility (bit reamer balance) and bit wear) , drilling stability (e.g., vibration levels along BHA, damaging vibration mode (whirling, stick-slip) , neutral point) , robustness (e.g., cumulative fatigue of drill string, drill string buckling, and overloading detection (predicted stress versus tool strength data) , measurement quality (e.g., survey rectification accounting for BHA sag, collar lateral displacement at MWD sensors) , borehole quality (e.g., hole tortuosity /hole microDLS /hole spiraling, and hole size variation) , directional tendency (e.g., Steering parameter sensitivity (WOB, SR, Cycle, FLOW, sliding/rotating distance) and other aspects of drilling (e.g., motor TF rectification accounting for drill string twist, stuck point depth estimation, and jarring impact) . The system may perform warning and advising to the drilling process including, pulling out of hole (POOH) based on high cumulative fatigue and severe cutting structure wear. The system may recommend to pull off bottom based on damaging whirling motion detected, excessive drill string buckling detected. The system may recommend a drilling parameter change based on high lateral/axial/torsional vibrations detected, poor borehole quality, challenging formation drilling (formation information based on LWD, mud logging, and the look-ahead detection of LWD) , poor directional control, poor weight distribution between bit and reamer, an undesired neutral point depth, and mild drill string buckling.

In one or more embodiments, the field management tool discussed above may be implemented as or execute on a computing system. The computing system may be combination of mobile, desktop, server, embedded, or other types of hardware. For example, as shown in FIG. 4, the computing system (400) may include one or more computer processor (s) (402) , associated memory (404) (e.g., random access memory (RAM) , cache memory, flash memory, etc. ) , one or more storage device (s) (406) (e.g., a hard disk, an optical drive such as a compact disk (CD) drive or digital versatile disk (DVD) drive, a flash memory stick, etc. ) , and numerous other elements and functionalities. The computer processor (s) (402) may be an integrated circuit for processing instructions. For example, the computer processor (s) may be one or more cores, or micro-cores of a processor. The computing system (400) may also include one or more input device (s) (410) , such as a touchscreen, keyboard, mouse, microphone, touchpad, electronic pen, or any other type of input device. Further, the computing system (400) may include one or more output device (s) (408) , such as a screen (e.g., a liquid crystal display (LCD) , a plasma display, touchscreen, cathode ray tube (CRT) monitor, projector, or other display device) , a printer, external storage, or any other output device. One or more of the output device (s) may be the same or different from the input device (s) . The computing system (400) may be connected to a network (412) (e.g., a local area network (LAN) , a wide area network (WAN) such as the Internet, mobile network, or any other type of network) via a network interface connection (not shown) . The input and output device (s) may be locally or remotely (e.g., via the network (412) ) connected to the computer processor (s) (402) , memory (404) , and storage device (s) (406) . Many different types of computing systems exist, and the aforementioned input and output device (s) may take other forms.

Software instructions in the form of computer readable program code to perform embodiments of the technology may be stored, in whole or in part, temporarily or permanently, on a non-transitory computer readable medium such as a CD, DVD, storage device, a diskette, a tape, flash memory, physical memory, or any other computer readable storage medium. Specifically, the software instructions may correspond to computer readable program code that when executed by a processor (s) , is configured to perform embodiments of the technology.

Further, one or more elements of the aforementioned computing system (400) may be located at a remote location and connected to the other elements over a network (412) . Further, embodiments of the technology may be implemented on a distributed system having a plurality of nodes, where each portion of the technology may be located on a different node within the distributed system. In one embodiment of the technology, the node corresponds to a distinct computing device. The node may correspond to a computer processor with associated physical memory. The node may correspond to a computer processor or micro-core of a computer processor with shared memory and/or resources.

The field management tool may further include a data repository. A data repository is any type of storage unit and/or device (e.g., a file system, database, collection of tables, or any other storage mechanism) for storing data. Further, the data repository may include multiple different storage units and/or devices. The multiple different storage units and/or devices may or may not be of the same type or located at the same physical site.

Fatigue is a cause of drill string failures and may account for more than 70％of the total failures. In many cases, drill pipe fatigue is progressive. In other words, cumulative damage occurs when the pipe is subjected to cycles of stress that accumulate damage to the equipment over time. The stress level for each cycle is generally lower than the tensile strength of material. Thus, fatigue failure may be sudden and unexpected. Fatigue may further have multiple stages including crack initiation, propagation, and fracture. One or more embodiments may develop a practical and effective calculation procedure to evaluate the fatigue life of drill pipe and BHA.

The sources of cyclic stress may include a rotating pipe or collar, rotating drill string when a part of the drill string is deformed, or bit/BHA backward whirling. For example, lateral deformation caused by buckling and backward whirling may worsen the condition. In an oversized hole, the drill string may tend to deform and bend more. FIG. 5.1 shows an example diagram (500) of the causes of fatigue. For example, compression stress (502) may be the compression of a portion of the drill string and tensile stress (504) may be the pulling on different ends of portion of the drill string. FIG. 5.2 shows an example diagram (510) of the cyclic stress over time. In particular, the x-axis (512) is time and the y-axis (514) is the amount of stress. The amplitude of the stress (518) is the amount the stress varies from the mean stress line (516) .

Fatigue limit, endurance limit, and fatigue strength may be used to describe the amplitude of cyclic stress that can be applied to the material without causing fatigue failure. An S-N curve may be generated to show the number of cycles to failure at a given stress amplitude. The S-N curve may be generated by experimental tests to obtain a number of points, and a best fit analysis may be performed on the points in order to determine the curve. FIG. 6 shows an example graph (600) of SN curves for steel and aluminum.

S-N curve is generally generated from fatigue test conducted under zero mean stress. In other words, the mean stress is assumed to be zero. To make use of the S-N curve under zero mean stress, equivalent bending stress amplitude may be calculated based on Goodman rule. The Goodman rule may be defined using equation (Eq. 1) .

In Eq. 1, σ_{alt_amp} is an actual stress amplitude, σ_mean is a mean stress, σ_ultimate is an ultimate tensile strength. σ_{equ_amp} is the bending stress amplitude and may be used to calculate cycle to fatigue in S-N curve. The peak stress value summed with the valley stress value as defined by the stress curve divided by two is the mean stress.

A realistic load history may have varying cyclic stress amplitude, mean stresses, and load frequencies. In other words, the amplitude of the stress may vary over time. Miner’s rule may be used to predict the cumulative fatigue damage due to a loading sequence that has different stress amplitudes. Equation (Eq. 2) provides the Miner’s rule.

In Eq. 2, D is cumulative fatigue damage, n_i is a number of cycles at the i^th stress amplitude, and N_i is a number of cycles to failure at the i^th stress amplitude from S-N curve.

FIG. 7 shows an example flowchart in accordance with one or more embodiments of the technology. While the various blocks in this flowchart are presented and described sequentially, one of ordinary skill will appreciate that some of the blocks may be executed in different orders, may be combined or omitted, and some of the blocks may be executed in parallel. Furthermore, the blocks may be performed actively or passively. For example, some blocks may be performed using polling or be interrupt driven in accordance with one or more embodiments of the technology. By way of an example, determination blocks may not require a processor to process an instruction unless an interrupt is received to signify that condition exists in accordance with one or more embodiments of the technology. As another example, determination blocks may be performed by performing a test, such as checking a data value to test whether the value is consistent with the tested condition in accordance with one or more embodiments of the technology.

In Block 701 of FIG. 7, the drilling interval is partitioned into sections. In Block 703, a drilling simulation is performed on each section to obtain stress results. The drilling simulation may be performed independently for each section to obtain the stress on the entire drill string. In Block 705, bending stress amplitude and mean stress is obtained from the stress results. In other words, for each depth, the stress amplitude and mean stress is obtained. In Block 707, the equivalent stress amplitude is calculated. For example, the Goodman rule, discussed above, may be used to calculate the equivalent stress amplitude. In Block 709, the number of cycles to failure is calculated based on the S-N curve based on the equivalent stress amplitude. In Block 711, the failure life consumption in each section is computed in accordance with one or more embodiments of the technology. The fatigue life consumption may be determined based on the equipment for each part. For example, the equipment manufacturer may specify the maximal amount of fatigue. By way of another example, the amount of fatigue may be determined using experimental data. In Block 713, the results across the sections are aggregated to obtain total fatigue life consumption in accordance with one or more embodiments of the technology. For example, the aggregation may be summing the results, generated based on weightings, obtaining a minimal or maximal value, or performing another aggregation.

FIG. 8 shows an example graph of performing Block 701 of FIG. 7 in accordance with one or more embodiments of the technology. For the example shown in FIG. 8, assume BHA depth in/out are the MD1 and MD2. The drilling interval [MD1, MD2] is divided into “m” sections. For example, the default section length ΔL may be 90 feet or one pipe stand. The default section length may be different without departing from the scope of the technology. Further, in some embodiments, a user may modify the section length. For example, a recommend length may be between 40 feet and 200 feet. Each segment S_i may have an end depth of D_i. Thus, D_i ＝ MD1+ i*ΔL, where ΔL is the length and i＝1…m-1. Further, the length of last section, S_m ＝ MD2-D_m-1. If the length of the last section is less than a threshold (e.g., ΔL/3) , then the last section may be combined with the adjacent section.

Further, one or more embodiments may be performed using static analysis and/or dynamic analysis. Static analysis considers stress though the borehole that is based on the curvature of the borehole, and the rotation count of the drill string in a borehole. In other words, each rotation has a certain amount of stress on the drill string that is caused by the curvature of the borehole combined with the rotation. By determining the number of cycles or rotations and the stress per cycle, the total fatigue life may be determined in the static analysis case.

Dynamic analysis considers stress from both the curvature of the borehole and the rotating drill string, and other sources of stress. For example, a drill string that is whipping through the borehole may have more stress than a simply rotating drill string. Thus, the whipping motion may cause more fatigue consumption over time. Thus dynamic analysis tracks stress on drill string using dynamic simulation. For example, sensor data may be used to calibrate a drilling model during drilling operation. Use simulations on the calibrated drilling model, the various stresses on the drill string are identified. Thus, fatigue consumption for the stress cycles of the drill string may be determined based on the various sources of stress using drilling simulation. In one or more embodiments, a drilling simulation is conducted at the end depth of each section, D_i. The simulation inputs at the i^th section Di may be WOB_i, RPM_i, and other inputs, such as motor flow rate, RSS steering command.

The static or dynamic fatigue life analysis in accordance with one or more aspects of the technology may be performed before and/or during drilling operations. For example, fatigue life management may be performed prior to drilling operations to generate a drilling plan that accommodates the fatigue life of the drill string. By way of another example, fatigue life management may be performed during drilling operations using sensor data to recalibrate a drilling model. The fatigue life management during drilling may be used to generate a warning when the amount of remaining fatigue life is less than a threshold or to provide an indicator as to when one or more parts on the drill string should be repaired or replaced.

Using the output of the simulation, the equivalent stress amplitude may be calculated using the Goodman rule as follows. Assume the stand pipe pressure in the i^th section is SPP_i. The mean stress component caused by the hydraulic pressure force may be calculated using equation (Eq. 3) .

In Eq. 3, ID and OD are the size of drill string components at which the fatigue calculation is conducted. The mean stress caused by axial force (σ_{mean_axial}) and hydraulic pressure force (σ_{mean_hydr}) may be summed using the following equation (Eq. 4) .

σ_mean＝σ_{mean_hydr}+σ_{mean_axial} (Eq. 4)

To account for the effect of mean stress, calculate the equivalent alternative stress amplitude σ_{equ_amp} using Goodman rule as shown in equation (Eq. 5) .

In Eq. 5, σ_ultimate may be set using a default value, such as 1000 ksi. Other default or non-default values may be used without departing from the scope of the claims.

Based on the equivalent stress amplitude, Block 709 of FIG. 7 may be performed. FIG. 9 shows an example graph (900) showing an example S-N curve for casings used for casing drilling. In FIG. 9, curve (906) corresponds to function (902) , and curve (908) corresponds to function (904) . As shown in FIG. 9, σ_{equ_amp}, the cycle to fatigue can be determined using the fitted S-N curve equation. The cycle to fatigue is N_i (h) at the location of h from bit based on the equivalent stress amplitude calculated from the simulation in the i^th section.

Block 711 of FIG. 7 may be performed, for example, as follows. The number of cycles for each stress level may be determined using Rain Flow Counting method. In the example n_i (h, s_k) is the number of cycles corresponding to equivalent alternative stress s_k. The endurance cycle to fatigue Ni (h, s_k) may be determined from the S-N curve. The fatigue life consumed in the i^th section at the location of distance h from bit may be calculated using the following equation (Eq. 6) .

Using Miner’s rule, the cumulative fatigue damage may be calculated using equation (Eq. 7) .

Thus, the total fatigue life may be presented to a drilling operator to determine when to repair or replace equipment on the drill string. Because removing the drill string from the borehole or having equipment failure in the borehole may lead to costly delays, by having an accurate estimate of drilling fatigue may increase profitability of the field.

While the technology has been described with respect to a limited number of embodiments, those skilled in the art, having benefit of this disclosure, will appreciate that other embodiments can be devised which do not depart from the scope of the technology as disclosed herein. Accordingly, the scope of the technology should be limited only by the attached claims.

Claims

A method for managing fatigue life comprising:

partitioning a well section into a plurality of sections；

calculating a stress value for each section of the plurality of sections；

calculating an equivalent stress amplitude for each section of the plurality of sections from the stress value；

computing a fatigue life consumption value in each section of the plurality of sections；

aggregating the fatigue life consumption value across the plurality of sections to obtain an aggregated fatigue life consumption value； and

presenting the aggregated fatigue life consumption value.
The method of claim 1, wherein the stress value is calculated using static analysis.
The method of claim 2, wherein the static analysis uses, for each section, a number of rotations per minute and an amount of time for each section.
The method of claim 1, wherein the stress value is calculated using dynamic analysis.
The method of claim 1, wherein the dynamic analysis comprises:

simulating stress of the drill string using a drilling model to generate the stress value.
The method of claim 5, wherein the dynamic analysis further comprises:

obtaining sensor data while drilling；

calibrating the drilling model using the sensor data to obtain a calibrated drilling model,

wherein stress of the drill string is performed using the calibrated drilling model.
The method of claim 1, further comprising:

generating a stress and number of cycles to failure (S-N) curve for each drilling component； and

calculating, for each component when drilling each section of the plurality of sections, number of stress cycles at different magnitudes,

wherein the fatigue life consumption is calculated using the stress cycles and S-N curve.
The method of claim 1, wherein aggregating the fatigue life consumption value comprises totaling the fatigue life consumption value across the plurality of sections.
A system for managing fatigue life comprising:

a computer processor； and

memory comprising instructions for:

partitioning a drill string into a plurality of sections；

calculating a stress value for each section of the plurality of sections；

calculating an equivalent stress amplitude for each section of the plurality of sections from the stress value；

computing a fatigue life consumption value in each section of the plurality of sections；

aggregating the fatigue life consumption value across the plurality of sections to obtain an aggregated fatigue life consumption value； and

presenting the aggregated fatigue life consumption value.
The system of claim 9, wherein the stress value is calculated using dynamic analysis.
The system of claim 9, wherein the dynamic analysis comprises:

simulating stress of the drill string using a drilling model to generate the stress value.
The system of claim 11, wherein the dynamic analysis further comprises:

obtaining sensor data while drilling；

calibrating the drilling model using the sensor data to obtain a calibrated drilling model,

wherein stress of the drill string is performed using the calibrated drilling model.
The system of claim 9, wherein the memory further comprises instructions for:

generating a stress and number of cycles to failure (S-N) curve for each drilling component； and

calculating, for each component when drilling each section of the plurality of sections, number of stress cycles at different magnitudes,

wherein the fatigue life consumption is calculated using the stress cycles and S-N curve.
The system of claim 9, wherein aggregating the fatigue life consumption value comprises totaling the fatigue life consumption value across the plurality of sections.
A non-transitory computer readable medium for managing fatigue life comprising computer readable program code for:

partitioning a drill string into a plurality of sections；

calculating a stress value for each section of the plurality of sections；

calculating an equivalent stress amplitude for each section of the plurality of sections from the stress value；

computing a fatigue life consumption value in each section of the plurality of sections；

aggregating the fatigue life consumption value across the plurality of sections to obtain an aggregated fatigue life consumption value； and

presenting the aggregated fatigue life consumption value.
The non-transitory computer readable medium of claim 15, wherein the stress value is calculated using dynamic analysis.
The non-transitory computer readable medium of claim 15, wherein the dynamic analysis comprises:

simulating stress of the drill string using a drilling model to generate the stress value.
The non-transitory computer readable medium of claim 17, wherein the dynamic analysis further comprises:

obtaining sensor data while drilling；

calibrating the drilling model using the sensor data to obtain a calibrated drilling model,

wherein stress of the drill string is performed using the calibrated drilling model.
The non-transitory computer readable medium of claim 19, further comprising computer readable program code for:

generating a stress and number of cycles to failure (S-N) curve for each drilling component； and

calculating, for each component when drilling each section of the plurality of sections, number of stress cycles at different magnitudes,

wherein the fatigue life consumption is calculated using the stress cycles and S-N curve.
The non-transitory computer readable medium of claim 15, wherein aggregating the fatigue life consumption value comprises totaling the fatigue life consumption value across the plurality of sections.