COMBINED SOFT AND STIFF-STRING TORQUE AND DRAG MODEL

Aspects of the disclosed technology provide techniques for determining frictional forces bearing on a downhole drill string. In some implementations, a method of the disclosed technology can include steps for segmenting a plurality of continuous nodes of the drilling string into a first segment and a second segment, computing a first set of values corresponding with one or more nodes in the first segment using a first model, computing a second set of values corresponding with one or more nodes in the second segment using a second model, and determining a torque of the drill string based on the first set of values and the second set of values. In some aspects, the method can further include steps for determining a drag force on the drill string based on the first set of values and the second set of values. Systems and machine-readable media are also provided.

TECHNICAL FIELD

The present disclosure relates generally to methods and apparatuses used in drilling wellbores for hydrocarbon production. More specifically, the disclosure relates to methods and systems for providing accurate wellbore placement by improving the accuracy of mathematical modeling of wellbore and drilling operations, including the estimation of torque and drag on a drill string.

BACKGROUND

To obtain hydrocarbons such as oil and gas, wellbores are typically drilled by rotating a drill bit that is attached at the end of the drill string. Modern drilling systems frequently employ a drill string having a bottom hole assembly and a drill bit at an end thereof. The drill bit is rotated by a downhole motor of the bottom hole assembly and/or by rotating the drill string. Pressurized drilling fluid is pumped through the drill string to power the downhole motor, provide lubrication and cooling to the drill bit and other components, and carry away formation cuttings.

A large proportion of drilling activity involves directional drilling, e.g., drilling deviated, branch, and/or horizontal wellbores. In directional drilling, wellbores are usually drilled along predetermined paths in order to increase the hydrocarbon production. As the drilling of the wellbore proceeds through various formations, the downhole operating conditions may change, and the operator must react to such changes and adjust parameters to maintain the predetermined drilling path and optimize the drilling operations. The drilling operator typically adjusts the surface-controlled drilling parameters, such as the weight on bit, drilling fluid flow through the drill string, the drill string rotational speed, and the density and/or viscosity of the drilling fluid, to affect the drilling operations.

DETAILED DESCRIPTION

Drilling operations are often conducted in accordance with one or more drilling or pre-drilling models of the subterranean conditions along the intended path of the wellbore. The following is a non-exclusive list of some of the variables various models may take into consideration: Wellbore properties, such as wellbore geometry, temperature and diameter versus the wellbore depth; friction, including dynamic and static friction coefficients throughout the wellbore; pressures, viscosities, densities, and flow rates of the fluids inside and outside of the drill string; material properties, such as strength and elastic modulus of the drill string components; inside and outside diameters along the length of the drill string; torque and force applied at the surface; tool properties, such as the length, outside diameter, stiffness, internal diameter, and flow restrictions in the tools being conveyed by the drill string, if any; and finally, the axial and rotational speeds of drill string and bit.

Computer-based models are sometimes used to calculate quantities such as the forces, stresses, torques, stretch, etc. associated with the drill string or other conveyances, such as coiled tubing, etc. Selection of the ideal model can depend on various factors; for example, soft-string, stiff-string, and finite element analysis (FEA) methods are different models that can be used to calculate torque and drag resulting from contact between the drill string and side walls of the wellbore.

Torque-drag modeling is commonly used to determine when the drill string is approaching a limit at which it may break or buckle; how much force, either tension or in compression, the drill string can apply at its downhole end; how much torque is being applied at the downhole end given a certain torque applied at surface; how much twist is in the drill string between the surface and the downhole end; the torsional and axial dynamic frequencies for stick-slip-type movements; and how much the drill string length will stretch or compress due to axial forces, twisting, temperature, pressure, and helical buckling, for example.

Understanding changes in drill string length can help to accurately calculate the depth of the drill string or the location of a tool it may be conveying. Similarly, knowledge of the amount of twist in a drill string can help ensure accurate tool face placement. For these reasons, mathematical simulations using torque-drag computer modeling programs provide useful data that is not available by simply monitoring drill string torque and hook loads at the surface.

However, not all torque and drag models are equally suitable in the same applications. For example, calculations using soft-string models are typically faster than those of stiff-string and FEA models. However, soft-string modeling omits considerations of element (string) stiffness, as well as the influence of hole size and radial clearance, and is therefore not suitable for applications in which the drill string is floating, or otherwise out of contact with the wellbore wall. Stiff-string and FEA methods, by contrast, are typically more accurate because a greater number of variables are considered, however, these models are computationally expensive, thereby limiting their suitability for real-time drilling and/or use in drilling automation.

Aspects of the disclosed technology, address the foregoing limitations of available torque-drag modeling by providing methodologies for using multiple models to compute an overall torque and/or drag on a drill string. In some embodiments, two or more different models may be used. For example, soft-string and stiff-string modeling techniques may be used (in combination) to compute torque-drag over different sections (segments) of the drill string. However, those of skill in the art will understand that the computational methods of the disclosed embodiments are not limited to the use of two model types, and that additional and/or other modeling techniques may be applied, without departing from the scope of the disclosed technology.

In some aspects, different model types (e.g., soft-string, stiff-string, and/or FEA) can be selectively applied to compute torque-drag parameters across different segments of a drill string. As such, methods of the disclosed technology provide mixed-modeling techniques that optimally utilize soft-string, stiff-string and/or FEA models in the calculation of torque and/or drag forces on a drill string. As discussed in further detail below, by optimally matching model types with different drill string segments (e.g., based on segment characteristics), the disclosed techniques can advantageously balance the tradeoffs between computational speed and accuracy, thereby enabling real-time torque-drag modeling necessary to facilitate drilling automation.

The disclosure now turns toFIGS.1A-B, andFIG.2to provide a brief introductory description of the larger systems that can be employed to practice the concepts, methods, and techniques disclosed herein. A more detailed description of the methods and systems for implementing the improved semblance processing techniques of the disclosed technology will then follow.

FIG.1Ashows an illustrative drilling environment100. Within environment100, drilling platform102supports derrick104having traveling block106for raising and lowering drill string108. Kelly110supports drill string108as it is lowered through rotary table112. Drill bit114is driven by a downhole motor and/or rotation of drill string108. As bit114rotates, it creates a borehole116that passes through various formations118. Pump120circulates drilling fluid through a feed pipe122to kelly110, downhole through the interior of drill string108, through orifices in drill bit114, back to the surface via the annulus around drill string108, and into retention pit124. The drilling fluid transports cuttings from the borehole into pit124and aids in maintaining borehole integrity.

Downhole tool126can take the form of a drill collar (i.e., a thick-walled tubular that provides weight and rigidity to aid the drilling process) or other arrangements known in the art. Further, downhole tool126can include various sensor and/or telemetry devices, including but not limited to: acoustic (e.g., sonic, ultrasonic, etc.) logging tools and/or one or more magnetic directional sensors (e.g., magnetometers, etc.). In this fashion, as bit114extends the borehole through formations118, the bottom-hole assembly (e.g., directional systems, and acoustic logging tools) can collect various types of logging data. For example, acoustic logging tools can include transmitters (e.g., monopole, dipole, quadrupole, etc.) to generate and transmit acoustic signals/waves into the borehole environment. These acoustic signals subsequently propagate in and along the borehole and surrounding formation and create acoustic signal responses or waveforms, which are received/recorded by evenly spaced receivers. These receivers may be arranged in an array and may be evenly spaced apart to facilitate capturing and processing acoustic response signals at specific intervals. The acoustic response signals are further analyzed to determine borehole and adjacent formation properties and/or characteristics.

For purposes of communication, a downhole telemetry sub128can be included in the bottom-hole assembly to transfer measurement data to surface receiver130and to receive commands from the surface. In some implementations, mud pulse telemetry may be used for transferring tool measurements to surface receivers and receiving commands from the surface; however, other telemetry techniques can also be used, without departing from the scope of the disclosed technology. In some embodiments, telemetry sub128can store logging data for later retrieval at the surface when the logging assembly is recovered. These logging and telemetry assemblies consume power, which must often be routed through the directional sensor section of the drill string, thereby producing stray EM fields which interfere with the magnetic sensors.

At the surface, surface receiver130can receive the uplink signal from downhole telemetry sub128and can communicate the signal to data acquisition module132. Module132can include one or more processors, storage mediums, input devices, output devices, software, and the like as described in further detail below. Module132can collect, store, and/or process the data received from tool126as described herein.

At various times during the drilling process, drill string108may be removed from the borehole as shown in example environment101, illustrated inFIG.1B. Once drill string108has been removed, logging operations can be conducted using a downhole tool134(i.e., a sensing instrument sonde) suspended by a conveyance142. In one or more embodiments, the conveyance142can be a cable having conductors for transporting power to the tool and telemetry from the tool to the surface. Downhole tool134may have pads and/or centralizing springs to maintain the tool near the central axis of the borehole or to bias the tool towards the borehole wall as the tool is moved downhole or uphole.

Downhole tool134can include various directional and/or acoustic logging instruments that collect data within borehole116. A logging facility144includes a computer system, such as those described with reference toFIGS.5and6, discussed below. In one or more embodiments, the conveyance142of downhole tool134can be at least one of wires, conductive or non-conductive cable (e.g., slickline, etc.), as well as tubular conveyances, such as coiled tubing, pipe string, or downhole tractor. Downhole tool134can have a local power supply, such as batteries, downhole generator and the like. When employing non-conductive cable, coiled tubing, pipe string, or downhole tractor, communication can be supported using, for example, wireless protocols (e.g. EM, acoustic, etc.), and/or measurements and logging data may be stored in local memory for subsequent retrieval.

AlthoughFIGS.1A and1Bdepict specific borehole configurations, it is understood that the present disclosure is equally well suited for use in wellbores having other orientations including vertical wellbores, horizontal wellbores, slanted wellbores, multilateral wellbores and the like. WhileFIGS.1A and1Bdepict an onshore operation, it should also be understood that the present disclosure is equally well suited for use in offshore operations. Moreover, the present disclosure is not limited to the environments depicted inFIGS.1A and1B, and can also be used in either logging-while-drilling (LWD) or measurement while drilling (MWD) operations.

FIG.2is a cut-away view of a wellbore environment200that includes drill string202having multiple continuous nodes2101-210N. Nodes2101-210Ncan represent nodes of a pipe or tool joint that are continuously repeated across the substantial length of drill string202. In the example of environment200, drill string202is shown to curve (dog-leg) within wellbore204, such that some of the nodes are in contact with a low-side of wellbore wall205A, whereas other nodes are in contact with a high-side of wellbore wall205B, and some of the nodes are floating. That is, the pipe-to-hole boundary206varies between different nodes, depending on their location/orientation within wellbore204. Because the suitability of different torque-drag models can vary based on node characteristics, a single model may not be optimally applied in the calculation of torque-drag values across all nodes2101-210N. As such, drill string202can be segmented by grouping nodes sharing similar characteristics. In the example of environment200, drill string202is divided into segments216,212, and214, each of which corresponds to a group of nodes similarly situated in wellbore204. By segmenting drill string202in node segments, different torque-drag models can be applied to different segments, depending on the corresponding segment characteristics.

In some aspects, segmenting can be performed based on user defined rules or parameters. For example, user defined inclination thresholds can be defined whereby positional deviations of the drill string exceeding the threshold are segmented into different segments. By way of example, user defined parameters may be used to segment portions of the drill string that dogleg more than15degrees per100feet of length, for example, indicating that the corresponding nodes may be out of contact with wellbore walls205.

In other aspects, segmentation may be informed using computations resulting from the application of one or more models across all nodes2101-210Nof drill string202. For example, a stiff-string model may be applied to identify locations (nodes) along drill string202where the stiff-string model is sub-optimal By knowing the node location within the path of the wellbore204, such calculations can be used to later segment drill string202as it is repositioned, e.g., by running in-hole.

Once drill string202is segmented, different models can be applied to determine torque-drag characteristics across different segments. In the example of drill string202, a soft-string model may be applied to segments216and214, whereas stiff-string (or FEA) modeling may be applied to the floating nodes corresponding with segment212. As discussed in further detail below, torque-drag calculations using mixed modeling techniques can require resolution of node characteristics, for example, to interpolate values derived from the separate models so that torque-drag contributions of each node can be correctly integrated across the string length.

FIG.3conceptually illustrates the combined use of different torque and drag models in the analysis of drill string force properties, according to some aspects of the technology. In the example ofFIG.3, initial modeling calculations302are represented graphically as drill string segments304A,306A,308A, and310A, along with the corresponding model used to perform the calculation. For example, segments304A,306A, and310A correspond with a stiff-string (or FEA) model, whereas segment308A corresponds with a soft-string model. By analyzing the force and/or displacement values for each node within the various segments, it can be determined what segments (if any) should be modeled using a different model type than what was initially used. In the example ofFIG.3, subsequent modeling calculations312, correspond with segments304B,306B,308B, and310B. In this example, stiff-string (or FEA) modeling applied to segment306A is revised to a soft-string model (segment306B). As such, segments306B and308B can be effectively merged based on common characteristics shared by an intervening node.

FIG.4is a process400for determining torque and/or drag on a drill string using a multi-model calculation, according to some aspects of the disclosed technology. Process400begins with step402in which a drill string is segmented into multiple segments, for example, into a first and second segments. As discussed above, segmentation can be based on user defined parameters, or based on calculated node characteristics determined using one or more torque-drag models, such as a stiff-string model.

In step404, a first set of values are computed using a first model, wherein the values correspond with one or more nodes in the first segment. In some aspects, computed node values may include force and or drag values for each node in the drill string. Additionally, the computed node values may include other node characteristics, such as a distance from the wellbore wall. By way of example, the first segment may include nodes that are abutting the wellbore wall, such as the nodes included in segment214, discussed above with respect toFIG.2. As such, the nodes in the first segment can be modeled using a soft-string model.

In step406, a second set of values are computed using a second model, wherein the values correspond with one or more nodes in the second segment. Similar to step404, the second set of values can represent characteristics of one or more nodes belonging to a different segment of the drill string, such as, segment202, discussed above with respect toFIG.2. As such, the model used to compute node characteristics for the second segment can be different from the model used to compute characteristics for nodes in the first segment. For example, the second model can include a stiff-string and/or FEA model, which is better suited for determining torque and/or drag characteristics for floating segments of the drill string.

In step408, a torque of the drill string is computed based on the first set of values and the second set of values. As discussed above, calculations using values resulting from the application of different models can require the resolution of boundary nodes. In some aspects, the resolution of boundary nodes can be performed automatically, for example, by comparing force, drag and/or wellbore-displacement characteristics amongst various boundary points to identify common (overlapping) nodes in the various value sets.

In step410, determining a drag force on the drill string based on the first set of values and the second set of values. In some aspects, steps408and410can be performed together, i.e., torque and drag calculations can be performed as one step. Alternatively, only torque and/or only drag calculations may be performed, depending on the desired implementation. It is understood that the foregoing descriptions of the use of two different models to compute node values for two different segments of drill string are intended to be illustrative, and not limiting in nature. Those of skill in the art will recognize that similar (or different) models may be used to compute node value characteristics for three or more drill string segments, without departing from the scope of the disclosed technology.

FIG.5is a block diagram of an example control system500that can be configured to apply multiple models in the calculation of drill string node characteristics, according to some aspects of the disclosed technology. Depending on the desired implementation, control system500may be implemented either on the surface of a drilling operation, or down-hole. In some aspects, control system500may be implemented using a combination of distributed hardware and/or firmware/software that resides on both the surface and down-hole.

As illustrated control system500comprises a processing system502that includes a torque and drag module504. Additionally, to facilitate the receipt and output/display of data, control system500can include input devices506, output510, and/or display508.

As discussed above, torque and drag module504can be configured to compute torque and drag forces on a drill string, or on portions of a drill string, for example, using different torque-drag model types. By implementing a hybrid calculation approach to torque-drag modeling, control system500can optimize speed and accuracy necessary for performing real-time modeling and necessary to enable drilling automation.

FIG.6illustrates an exemplary computing system700for use with example tools and systems (e.g., tool126). The more appropriate embodiment will be apparent to those of ordinary skill in the art when practicing the present technology. Persons of ordinary skill in the art will also readily appreciate that other system embodiments are possible.

Specifically,FIG.6illustrates system architecture600wherein the components of the system are in electrical communication with each other using a bus605. System architecture600can include a processing unit (CPU or processor)610, as well as a cache612, that are variously coupled to system bus605. Bus605couples various system components including system memory615, (e.g., read only memory (ROM)620and random access memory (RAM)625), to processor610. System architecture600can include a cache of high-speed memory connected directly with, in close proximity to, or integrated as part of the processor610. System architecture600can copy data from the memory615and/or the storage device630to the cache612for quick access by the processor610. In this way, the cache can provide a performance boost that avoids processor610delays while waiting for data. These and other modules can control or be configured to control the processor610to perform various actions. Other system memory615may be available for use as well. Memory615can include multiple different types of memory with different performance characteristics. Processor610can include any general-purpose processor and a hardware module or software module, such as module1(632), module2(634), and module3(636) stored in storage device630, configured to control processor610as well as a special-purpose processor where software instructions are incorporated into the actual processor design. Processor610may essentially be a completely self-contained computing system, containing multiple cores or processors, a bus, memory controller, cache, etc. A multi-core processor may be symmetric or asymmetric.

Storage device630is a non-volatile memory and can be a hard disk or other types of computer readable media which can store data that are accessible by a computer, such as magnetic cassettes, flash memory cards, solid state memory devices, digital versatile disks, cartridges, random access memories (RAMs)635, read only memory (ROM)620, and hybrids thereof.

Storage device630can include software modules632,634,636for controlling the processor610. Other hardware or software modules are contemplated. The storage device630can be connected to the system bus605. In one aspect, a hardware module that performs a particular function can include the software component stored in a computer-readable medium in connection with the necessary hardware components, such as the processor610, bus605, output device642, and so forth, to carry out various functions of the disclosed technology.

STATEMENTS OF THE DISCLOSURE

Statement 1: a computer-implemented method for determining frictional force on a downhole drilling string, the method comprising: segmenting a plurality of continuous nodes of the drilling string into a first segment and a second segment; computing a first set of values corresponding with one or more nodes in the first segment using a first model; computing a second set of values corresponding with one or more nodes in the second segment using a second model, and wherein the first model is different from the second model; and determining a torque of the drill string based on the first set of values and the second set of values.

Statement 2: the computer-implemented method of statement 1, further comprising: determining a drag force on the drill string based on the first set of values and the second set of values.

Statement 3: the computer-implemented method of any of statements 1-2, wherein segmenting the plurality of continuous nodes is performed based on user provided parameters.

Statement 4: the computer-implemented method of statements 1-3, wherein segmenting the plurality of continuous nodes is performed based on characteristics for one or more of the plurality of continuous nodes determined by a stiff-string model.

Statement 5: the computer-implemented method of statements 1-4, wherein the first model is a soft-string model.

Statement 6: the computer-implemented method of any of statements 1-5, wherein the second model is a stiff-string model.

Statement 7: the computer-implemented method of statements 1-6, wherein the second model utilizes finite element analysis.

Statement 8: a system for determining frictional forces bearing on a downhole drill string, the system comprising: one or more processors; and a non-transitory memory coupled to the one or more processors, wherein the memory comprises instruction configured to cause the processors to perform operations for: segmenting a plurality of continuous nodes of the drilling string into a first segment and a second segment; computing a first set of values corresponding with one or more nodes in the first segment using a first model; computing a second set of values corresponding with one or more nodes in the second segment using a second model, and wherein the first model is different from the second model; and determining a torque of the drill string based on the first set of values and the second set of values.

Statement 9: the system of statement 8, wherein the processors are further configured to perform operations comprising: determining a drag force on the drill string based on the first set of values and the second set of values.

Statement 10: the system of any of statements 8-9, wherein segmenting the plurality of continuous nodes is performed based on user provided parameters.

Statement 11: the system of any of statements 8-10, wherein segmenting the plurality of continuous nodes is performed based on characteristics for one or more of the plurality of continuous nodes determined by a stiff-string model.

Statement 12: the system of any of statements 8-11: wherein the first model is a soft-string model.

Statement 13: the system of statements 8-12, wherein the second model is a stiff-string model.

Statement 14: the system of statements 8-13, wherein the second model utilizes finite element analysis.

Statement 15: a tangible, non-transitory, computer-readable media having instructions encoded thereon, the instructions, when executed by a processor, are operable to perform operations for: segmenting a plurality of continuous nodes of a drilling string into a first segment and a second segment; computing a first set of values corresponding with one or more nodes in the first segment using a first model; computing a second set of values corresponding with one or more nodes in the second segment using a second model, and wherein the first model is different from the second model; and determining a torque of the drill string based on the first set of values and the second set of values.

Statement 16: the tangible, non-transitory, computer-readable media of statement 15, wherein the processors are further operable to perform operations comprising: determining a drag force on the drill string based on the first set of values and the second set of values.

Statement 17: the tangible, non-transitory, computer-readable media of any of statements 15-16, wherein segmenting the plurality of continuous nodes is performed based on user provided parameters.

Statement 18: the tangible, non-transitory, computer-readable media of any of statements 15-17, wherein segmenting the plurality of continuous nodes is performed based on characteristics for one or more of the plurality of continuous nodes determined by a stiff-string model.

Statement 19: the tangible, non-transitory, computer-readable media of statements 15-18, wherein the first model is a soft-string model or a stiff-string model.

Statement 20: the tangible, non-transitory, computer-readable media of statements 15-19, wherein the second model utilizes finite element analysis.