A downhole parameter space generation method, device and equipment based on formation constraint

Abstract

This specification relates to the technical field of downhole parameter prediction, and provides a method, device and equipment for generating downhole parameter space based on formation constraints. The method includes: interpolating the work area according to the well position data and formation data of known wells in the work area to obtain the formation distribution of the work area; selecting a point to be predicted in the work area, and determining the mapping point of the point to be predicted according to the formation distribution; the mapping point is the position point on the known well that is located in the same formation as the point to be predicted and has a corresponding position; determining the influence factor of the known well on the point to be predicted; predicting the downhole parameters of the point to be predicted according to the downhole parameters of the mapping point and the influence factor; predicting the downhole parameters of the remaining points to be predicted in the work area; and generating a downhole parameter distribution map of the work area according to the downhole parameters of each point to be predicted in the work area. The embodiments of this specification can improve the accuracy of downhole parameter prediction while reducing the implementation cost.

Description

Technical Field

[0001] This specification relates to the technical field of downhole parameter prediction, and in particular, to a method, device, and equipment for generating downhole parameter space based on formation constraints. Background Art

[0002] Downhole parameters (such as logging data and drilling data) are important reference bases for drilling engineering. Currently, the acquisition of downhole parameters is mainly obtained by processing logging data of exploration wells. The downhole parameters obtained in this way are only meaningful for this well and extremely adjacent undrilled wells, and cannot be directly applied to mining plans at relatively long distances. If one wants to obtain logging data in a new undrilled area, it is often necessary to drill exploration wells in this new undeveloped area and collect data, which requires high costs. If the interval where the well is to be drilled is between several existing wells, the existing methods can combine data such as adjacent wells and seismic data to predict the downhole parameters at this location to guide the drilling engineer and the steering engineer to carry out drilling operations. However, most of the existing formation parameter and downhole parameter prediction schemes do not consider the influencing factors brought by formation information, and their prediction results have large deviations from the actual results. In most cases, they cannot provide sufficient reference, and it becomes inevitable to drill exploration wells, but this significantly increases the cost. Summary of the Invention

[0003] The purpose of the embodiments of this specification is to provide a method, device, and equipment for generating downhole parameter space based on formation constraints, so as to improve the accuracy of downhole parameter space generation while reducing implementation costs.

[0004] To achieve the above object, on the one hand, the embodiments of this specification provide a method for generating downhole parameter space based on formation constraints, including:

[0005] Interpolating the work area according to the well position data and formation data of known wells in the work area to obtain the formation distribution of the work area;

[0006] Select a point to be predicted in the work area, and determine the mapping point of the point to be predicted according to the formation distribution; the mapping point is the position point on the known well that is located in the same formation as the point to be predicted and has a corresponding position;

[0007] Determine the influence factor of the known well on the point to be predicted;

[0008] Predict the downhole parameters of the point to be predicted according to the downhole parameters of the mapping point and the influence factor;

[0009] Predict the downhole parameters of the remaining points to be predicted in the work area;

[0010] Generate the downhole parameter distribution map of the work area based on the downhole parameters of each prediction point in the work area.

[0011] In the method for generating the downhole parameter space based on formation constraints according to the embodiments of the present specification, determining the influence factor of the known well on the prediction point includes:

[0012] Determine the influence factor of the known well on the prediction point according to the horizontal distance between the prediction point and the known well.

[0013] In the method for generating the downhole parameter space based on formation constraints according to the embodiments of the present specification, interpolating the work area based on the well position data and formation data of the known wells in the work area includes:

[0014] Uniformly divide the work area into a network according to the coordinate range of the work area;

[0015] Calculate the horizontal distances between the azimuth coordinates of all known wells and the spatial grid points at the positions of non-known wells respectively, and use the reciprocal of each horizontal distance as the vertical depth influence weight of each known well on each spatial grid point;

[0016] Calculate the total sum of the vertical depth influence weights of each spatial grid point;

[0017] For the same formation boundary point of the known well, according to the formula Calculate the vertical depth of the same formation boundary of the spatial grid point;

[0018] Among them, is the vertical depth of the same formation boundary of the spatial grid point, z i is the i-th same formation boundary point of the known well, d i is the distance between the i-th known well and the i-th spatial grid, Q i is the total sum of the vertical depth influence weights of the i-th spatial grid point, and n is the number of known wells.

[0019] In the method for generating the downhole parameter space based on formation constraints according to the embodiments of the present specification, determining the mapping point of the prediction point according to the formation distribution includes:

[0020] Determine the formation to which the prediction point belongs according to the formation distribution;

[0021] Determine the vertical position of the prediction point in the formation;

[0022] Determine the well sections of all known wells located in the formation;

[0023] Determine the vertical position corresponding to the same ratio as the prediction point in each well section, and use this vertical position as the mapping point of the prediction point.

[0024] In the method for generating the downhole parameter space based on formation constraint according to the embodiments of this specification, determining the influence factor of the known well on the to-be-predicted point according to the horizontal distance between the to-be-predicted point and the known well includes:

[0025] According to the formula Determine the influence factor of the known well on the to-be-predicted point;

[0026] Wherein, Z facter Is the influence factor of the known well on the to-be-predicted point, d i Is the distance between the i-th known well and the i-th spatial grid, Q i Is the total vertical depth influence weight of the i-th spatial grid point, and n is the number of known wells.

[0027] In the method for generating the downhole parameter space based on formation constraint according to the embodiments of this specification, predicting the downhole parameter of the to-be-predicted point according to the downhole parameter of the mapped point and the influence factor includes:

[0028] Determine the product of the downhole parameter of each mapped point and the influence factor of the corresponding known well;

[0029] Accumulate each of the products to obtain the downhole parameter of the to-be-predicted point.

[0030] In the method for generating the downhole parameter space based on formation constraint according to the embodiments of this specification, after determining the downhole parameters of the remaining to-be-predicted points in the work area, it further includes:

[0031] Generate a downhole parameter line chart of a specified area in the work area.

[0032] On the other hand, the embodiments of this specification also provide a device for generating the downhole parameter space based on formation constraint, including:

[0033] An interpolation module, configured to perform interpolation on the work area according to the well position data and formation data of the known wells in the work area to obtain the formation distribution of the work area;

[0034] A mapping module, configured to select a to-be-predicted point in the work area and determine the mapped point of the to-be-predicted point according to the formation distribution; the mapped point is the position point on the known well that is located in the same formation as the to-be-predicted point and has a corresponding position;

[0035] A determination module, configured to determine the influence factor of the known well on the to-be-predicted point;

[0036] A prediction module, configured to predict the downhole parameter of the to-be-predicted point according to the downhole parameter of the mapped point and the influence factor, and predict the downhole parameters of the remaining to-be-predicted points in the work area;

[0037] A generation module, configured to generate a downhole parameter distribution map of the work area according to the downhole parameters of each point to be predicted in the work area.

[0038] On the other hand, an embodiment of the present specification further provides a computer device, including a memory, a processor, and a computer program stored on the memory. When the computer program is run by the processor, it executes the instructions of the above method.

[0039] On the other hand, an embodiment of the present specification further provides a computer storage medium, on which a computer program is stored. When the computer program is run by the processor of a computer device, it executes the instructions of the above method.

[0040] As can be seen from the technical solutions provided by the embodiments of the present specification above, in the embodiments of the present specification, based on the well position data and formation data of the known wells in the work area, formation interpolation is performed on the entire work area to obtain approximate actual formation information; on this basis, according to the downhole parameters of the known wells, mapping points of the selected points to be predicted are found (that is, the position points on the known wells that are located in the same formation as the point to be predicted and have corresponding positions), and the downhole parameters of the point to be predicted are estimated according to the downhole parameters of the mapping points and the influence factors of the known wells on the point to be predicted. In this way, the downhole parameters of each point to be predicted in the work area can be obtained, and thus a downhole parameter distribution map of the entire work area can be generated accordingly. Since when predicting the downhole parameters of each point to be predicted in the work area, not only the formation distribution information in the work area is considered, but also the influence factors of the downhole parameters of the known wells in the work area on the point to be predicted are considered, the accuracy of downhole parameter prediction is improved; moreover, compared with the prior art in which a large number of drillings are carried out to determine downhole parameters, the cost of the method for generating downhole parameter space implemented by computer algorithms in the embodiments of the present specification is lower, which is beneficial to accelerating the realization of intelligent drilling. Description of the Drawings

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present specification or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments recorded in the present specification. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts. In the drawings:

[0042] Figure 1 A flowchart of a method for generating downhole parameter space based on formation constraints in some embodiments of the present specification is shown;

[0043] Figure 2 A schematic diagram of the well position data and formation data of known wells in an embodiment of the present specification is shown;

[0044] Figure 3 Shows the schematic diagram of the formation distribution obtained by interpolation in an embodiment of this specification;

[0045] Figure 4 Shows the schematic diagram of selecting the point to be predicted in an embodiment of this specification;

[0046] Figure 5 Shows the schematic diagram of determining the mapping point according to the point to be predicted in an embodiment of this specification;

[0047] Figure 6 Shows the schematic diagram of the downhole parameter distribution in an embodiment of this specification;

[0048] Figure 7 Shows the broken line schematic diagram of the downhole parameters in the specified area in an embodiment of this specification;

[0049] Figure 8 Shows the structural block diagram of the downhole parameter space generation device based on formation constraints in some embodiments of this specification;

[0050] Figure 9 Shows the structural block diagram of the computer device in some embodiments of this specification.

[0051]

Explanation of the reference numerals

[0052] 81, Interpolation module;

[0053] 82, Mapping module;

[0054] 83, Determination module;

[0055] 84, Prediction module;

[0056] 85, Generation module;

[0057] 902, Computer device;

[0058] 904, Processor;

[0059] 906, Memory;

[0060] 908, Driving mechanism;

[0061] 910, Input / output interface;

[0062] 912, Input device;

[0063] 914, Output device;

[0064] 916, Presentation device;

[0065] 918, Graphical user interface;

[0066] 920, Network interface;

[0067] 922. Communication link;

[0068] 924. Communication bus. Specific implementation manner

[0069] In order to enable those skilled in the art of this technology to better understand the technical solutions in this specification, the following will clearly and completely describe the technical solutions in the embodiments of this specification in conjunction with the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of this specification, rather than all the embodiments. Based on the embodiments in this specification, all other embodiments obtained by those of ordinary skill in the art without making creative efforts should belong to the scope protected by this specification.

[0070] An underground parameter space generation method based on formation constraint is provided in the embodiments of this specification, which can be applied to any suitable computer device. Refer to Figure 1 As shown, in some embodiments, the underground parameter space generation method based on formation constraint may include the following steps:

[0071] Step 101: Interpolate the work area according to the well position data and formation data of the known wells in the work area to obtain the formation distribution of the work area.

[0072] Step 102: Select a point to be predicted in the work area, and determine the mapping point of the point to be predicted according to the formation distribution; the mapping point is the position point on the known well that is located in the same formation as the point to be predicted and has a corresponding position.

[0073] Step 103: Determine the influence factor of the known well on the point to be predicted.

[0074] Step 104: Predict the underground parameters of the point to be predicted according to the underground parameters of the mapping point and the influence factor.

[0075] Step 105: Predict the underground parameters of the remaining points to be predicted in the work area.

[0076] Step 106: Generate an underground parameter distribution map of the work area according to the underground parameters of each point to be predicted in the work area.

[0077] In the embodiments of this specification, based on the well location data and formation data of known wells in the work area, the entire work area is interpolated for the formation to obtain approximate actual formation information. On this basis, according to the downhole parameters of the known wells, the mapping points of the selected prediction points to be predicted are found (i.e., the position points on the known wells that are located in the same formation as the prediction point to be predicted and have corresponding positions), and the downhole parameters of the prediction point to be predicted are estimated based on the downhole parameters of the mapping points and the influence factors of the known wells on the prediction point to be predicted. In this way, the downhole parameters of each prediction point in the work area can be obtained, and thus the downhole parameter distribution map of the entire work area can be generated accordingly. When predicting the downhole parameters of each prediction point in the work area, not only the formation distribution information in the work area is considered, but also the influence factors of the downhole parameters of the known wells in the work area on the prediction point to be predicted are considered, thereby improving the accuracy of downhole parameter prediction; moreover, compared with the prior art in which a large number of drillings are carried out to determine the downhole parameters, the cost of this method for generating downhole parameters in space through computer algorithms in the embodiments of this specification is lower, which is conducive to accelerating the realization of intelligent drilling.

[0078] In the embodiments of this specification, a known well refers to a well that has been drilled in the work area. Through the logging data, drilling data, core analysis results, etc. of the known well, the well location data, formation data, and downhole parameters at the location of the known well can be obtained. Among them, the well location data refers to the geographical location coordinates of the well (such as longitude and latitude) or relative coordinates, etc. The formation data refers to the formation information of the well in the vertical depth (i.e., vertical depth) direction, which can be a stratigraphic time scale or stratigraphic section division data with the same attributes, etc. The downhole parameters can include logging data, drilling data, etc.

[0079] By interpolating the work area based on the well location data and formation data of the known wells in the work area, approximate actual formation information of the entire work area can be obtained. In some embodiments, interpolating the work area based on the well location data and formation data of the known wells in the work area may include the following steps:

[0080] (1) Uniformly network-divide the work area according to the coordinate range of the work area.

[0081] (2) Calculate the horizontal distances between the azimuth coordinates of all known wells and the spatial grid points at the positions of each non-known well respectively, and use the reciprocal of each horizontal distance as the vertical depth influence weight of each known well on each spatial grid point. The closer the spatial grid point is to the known well, the greater its influence on the vertical depth by the known well, and vice versa. Therefore, the reciprocal of each horizontal distance can be used as the vertical depth influence weight of each known well on each spatial grid point.

[0082] For example, when a spatial grid point is x and the known wells are w1, w2, and w3 respectively, the horizontal distances between the spatial grid point x and the known wells w1, w2, and w3 can be calculated as: d1, d2, and d3. Then, the vertical depth influence weights of the known wells w1, w2, and w3 on the spatial grid point x can be respectively expressed as: 1 / d1, 1 / d2, and 1 / d3.

[0083] (3) Calculate the total vertical depth influence weight of each of the spatial grid points.

[0084] For any spatial grid point, the sum of the vertical depth influence weights of all the drilled wells in the work area on it is the total vertical depth influence weight. Taking the above-mentioned spatial grid point x and the known wells w1, w2, and w3 as an example, the total vertical depth influence weight of the spatial grid point x can be expressed as Q = 1 / d1 + 1 / d2 + 1 / d3.

[0085] (4) For the same formation boundary point of the known well, according to the formula Calculate the vertical depth of the same formation boundary of the spatial grid point.

[0086] Wherein, is the vertical depth of the same formation boundary of the spatial grid point, z i is the i-th same formation boundary point of the known well, d i is the distance between the i-th known well and the i-th spatial grid, Q i is the total vertical depth influence weight of the i-th spatial grid point, and n is the number of known wells.

[0087] For example, in the exemplary embodiment as Figure 2 shown, there are three known wells (Well 1, Well 2, and Well 3) in a work area, and the well location data of the three known wells can be as Figure 2 shown. Through the interpolation means of the embodiments of this specification, a formation distribution map as Figure 3 shown can be obtained.

[0088] The interpolation means of the embodiments of this specification is a method similar to Kriging interpolation. In addition, in some other embodiments, according to the formation conditions, a certain function can also be used to fit each formation boundary to make the predicted formation conditions smoother and more in line with the actual formation conditions, so as to reduce errors.

[0089] In some embodiments, a point to be predicted can be selected from the work area by means of sequential selection or random selection, etc. Among them, the point to be predicted is a spatial grid point with unknown downhole parameters. The determining the mapping point of the point to be predicted according to the formation distribution may include the following steps:

[0090] (1) Determine the formation to which the point to be predicted belongs according to the formation distribution.

[0091] On the basis of a uniformly networked and stratified formation distribution, when a point to be predicted is selected, the formation to which the point to be predicted belongs is determined, that is, the formation to which the point to be predicted belongs can be determined according to the formation distribution.

[0092] (2) Determine the vertical position of the point to be predicted in the formation.

[0093] The vertical position of the point to be predicted in the formation to which it belongs is the position distribution of the point to be predicted in the vertical direction (i.e., the depth direction) in the formation to which it belongs. For example, in the exemplary embodiment shown in Figure 4 If the point to be predicted is located in Formation 2, then the distance from the point to be predicted vertically to the top of Formation 2 and the distance from the point to be predicted vertically to the bottom of Formation 2 can be determined. Assume that the distance from the point to be predicted vertically to the top of Formation 2 is 100 meters and the distance from the point to be predicted vertically to the bottom of Formation 2 is 200 meters, then the vertical position of the point to be predicted in Formation 2 is the one-third (1 / 3) depth position in Formation 2.

[0094] (3) Determine the well sections of all known wells located in the formation.

[0095] That is, determine the well sections of all known wells located in the formation to which the point to be predicted belongs. For example, in the exemplary embodiment shown in Figure 5 The well sections of all known wells in Formation 2 to which the point to be predicted belongs include: the well section of Well 1 in Formation 2, the well section of Well 2 in Formation 2, and the well section of Well 3 in Formation 2.

[0096] (4) Determine the vertical positions corresponding to the same ratio as the point to be predicted in each of the well sections, and use this vertical position as the mapping point of the point to be predicted.

[0097] For example, in the exemplary embodiment shown in Figure 5 If the vertical position of the point to be predicted in Formation 2 is the one-third depth position in Formation 2, then in the well section of Well 1 in Formation 2, the point at the one-third depth position in Formation 2 in this well section can be found and used as the mapping point 1 of the point to be predicted; in the well section of Well 2 in Formation 2, the point at the one-third depth position in Formation 2 in this well section can be found and used as the mapping point 2 of the point to be predicted; and in the well section of Well 3 in Formation 2, the point at the one-third depth position in Formation 2 in this well section can be found and used as the mapping point 3 of the point to be predicted.

[0098] In some embodiments, determining the influence factor of the known well on the point to be predicted means: determining the influence factor of the known well on the point to be predicted according to the horizontal distance between the point to be predicted and the known well. For example, the influence factor of the known well on the point to be predicted can be determined according to the horizontal distance between the point to be predicted and the known well. Specifically, it can be determined according to the formula to determine the influence factor of the known well on the point to be predicted; where Z facter is the influence factor of the known well on the point to be predicted, d i is the distance between the i-th known well and the i-th spatial grid, Q i is the total vertical depth influence weight of the i-th spatial grid point, and n is the number of known wells. For specific details, reference can be made to the description of the above difference part, which will not be elaborated here.

[0099] In some embodiments, predicting the downhole parameters of the point to be predicted according to the downhole parameters of the mapping point and the influence factor may include the following steps:

[0100] (1) Determine the product of the downhole parameters of each mapping point and the influence factor of the corresponding known well.

[0101] For example, in the exemplary embodiment as shown in Figure 5 , assuming that the downhole parameters of mapping point 1, mapping point 2, and mapping point 3 are a, b, and c respectively, and the influence factors of well 1, well 2, and well 3 are z1, z2, and z3 respectively, then:

[0102] The product of the downhole parameter of mapping point 1 and the influence factor of the corresponding known well is: a×z1;

[0103] The product of the downhole parameter of mapping point 2 and the influence factor of the corresponding known well is: b×z2;

[0104] The product of the downhole parameter of mapping point 3 and the influence factor of the corresponding known well is: c×z3.

[0105] (2) Accumulate the products to obtain the downhole parameters of the point to be predicted.

[0106] For example, in the exemplary embodiment as shown in Figure 5 , assuming that the downhole parameters of mapping point 1, mapping point 2, and mapping point 3 are a, b, and c respectively, and the influence factors of well 1, well 2, and well 3 are z1, z2, and z3 respectively, then the downhole parameter Y of the point to be predicted can be expressed as: Y = a×z1 + b×z2 + c×z3.

[0107] By repeating the above steps 102 to 104, the downhole parameters of the remaining points to be predicted in the work area can be predicted. On this basis, the downhole parameter distribution map of the entire work area can be drawn. For example, in an exemplary embodiment, the downhole parameter distribution map of the entire work area can be as shown in Figure 6 shown. In the downhole parameter distribution in Figure 6 , the color is inversely proportional to the downhole parameter value, that is, the darker the color, the smaller the corresponding downhole parameter value.

[0108] In other embodiments, on the basis of obtaining the downhole parameters of each point to be predicted in the work area, a downhole parameter broken line of a specified area in the work area can be selectively drawn as needed (as shown in Figure 7 ), and it is compared with the measured downhole parameter broken line to facilitate intuitively judging the accuracy of the prediction result.

[0109] Although the process flow described above includes multiple operations that appear in a specific order, it should be clearly understood that these processes may include more or fewer operations, and these operations may be executed sequentially or in parallel (for example, using a parallel processor or a multi-threaded environment).

[0110] Corresponding to the above-described method for generating a downhole parameter space based on formation constraints, an embodiment of the present specification further provides a device for generating a downhole parameter space based on formation constraints. Referring to Figure 8 shown, the device for generating a downhole parameter space based on formation constraints may include: an interpolation module 81, a mapping module 82, a determination module 83, a prediction module 84, and a generation module 85. Among them:

[0111] The interpolation module 81 may be configured to interpolate the work area according to the well position data and formation data of the known wells in the work area to obtain the formation distribution of the work area;

[0112] The mapping module 82 may be configured to select a point to be predicted in the work area and determine the mapping point of the point to be predicted according to the formation distribution; the mapping point is the position point on the known well that is located in the same formation as the point to be predicted and has a corresponding position;

[0113] The determination module 83 may be configured to determine the influence factor of the known well on the point to be predicted;

[0114] The prediction module 84 may be configured to predict the downhole parameters of the point to be predicted according to the downhole parameters of the mapping point and the influence factor, and predict the downhole parameters of the remaining points to be predicted in the work area;

[0115] The generation module 85 may be configured to generate a downhole parameter distribution map of the work area according to the downhole parameters of each point to be predicted in the work area.

[0116] In some embodiments of the downhole parameter space generation device based on formation constraints, the determining module 83 determines the influence factor of the known well on the point to be predicted, including:

[0117] Determining the influence factor of the known well on the point to be predicted according to the horizontal distance between the point to be predicted and the known well.

[0118] In some embodiments of the downhole parameter space generation device based on formation constraints, the interpolation module 81 interpolates the work area according to the well position data and formation data of the known wells in the work area, including:

[0119] Uniformly dividing the work area into a network according to the coordinate range of the work area;

[0120] Calculating the horizontal distance between the azimuth coordinates of all known wells and the spatial grid points at each non-known well position respectively, and taking the reciprocal of each horizontal distance as the vertical depth influence weight of each known well on each spatial grid point;

[0121] Calculating the total sum of the vertical depth influence weights of each spatial grid point;

[0122] For the same formation demarcation point of the known well, according to the formula Calculating the vertical depth of the same formation demarcation of the spatial grid point;

[0123] Wherein, is the vertical depth of the same formation demarcation of the spatial grid point, z i is the i-th same formation demarcation point of the known well, d i is the distance between the i-th known well and the i-th spatial grid, Q i is the total sum of the vertical depth influence weights of the i-th spatial grid point, and n is the number of known wells.

[0124] In some embodiments of the downhole parameter space generation device based on formation constraints, the mapping module 82 determines the mapping point of the point to be predicted according to the formation distribution, including:

[0125] Determining the formation to which the point to be predicted belongs according to the formation distribution;

[0126] Determining the vertical position of the point to be predicted in the formation;

[0127] Determining the well sections of all known wells located in the formation;

[0128] Determining the vertical position corresponding to the same ratio as the point to be predicted in each well section, and taking this vertical position as the mapping point of the point to be predicted.

[0129] In some embodiments of the downhole parameter space generation device based on formation constraints, the determining module 83 determines the influence factor of the known well on the to-be-predicted point according to the horizontal distance between the to-be-predicted point and the known well, including:

[0130] Determine the influence factor of the known well on the to-be-predicted point according to the formula ;

[0131] where Z facter is the influence factor of the known well on the to-be-predicted point, d i is the distance between the i-th known well and the i-th spatial grid, Q i is the total vertical depth influence weight of the i-th spatial grid point, and n is the number of known wells.

[0132] In some embodiments of the downhole parameter space generation device based on formation constraints, the prediction module 84 predicts the downhole parameters of the to-be-predicted point according to the downhole parameters of the mapped point and the influence factor, including:

[0133] Determine the product of the downhole parameters of each mapped point and the influence factor of the corresponding known well;

[0134] Accumulate the products to obtain the downhole parameters of the to-be-predicted point.

[0135] In some embodiments of the downhole parameter space generation device based on formation constraints, the generation module 85 can also be used for:

[0136] After determining the downhole parameters of the remaining to-be-predicted points in the work area, generate a broken line graph of the downhole parameters of a specified area in the work area.

[0137] For the convenience of description, when describing the above device, various units are described separately according to their functions. Of course, when implementing this specification, the functions of each unit can be implemented in one or more software and / or hardware.

[0138] The embodiments of this specification also provide a computer device. As Figure 9As shown, in some embodiments of this specification, the computer device 902 may include one or more processors 904, such as one or more central processing units (CPUs) or graphics processing units (GPUs), and each processing unit may implement one or more hardware threads. The computer device 902 may also include any memory 906 for storing any kind of information such as code, settings, data, etc. In a specific embodiment, a computer program stored on the memory 906 and executable on the processor 904, when run by the processor 904, may execute the instructions of the downhole parameter space generation method described in any of the above embodiments. Non-limitingly, for example, the memory 906 may include any one or more combinations of the following: any type of RAM, any type of ROM, flash memory devices, hard disks, optical discs, etc. More generally, any memory may use any technology to store information. Further, any memory may provide volatile or non-volatile retention of information. Further, any memory may represent a fixed or removable component of the computer device 902. In one case, when the processor 904 executes the associated instructions stored in any memory or combination of memories, the computer device 902 may perform any operation of the associated instructions. The computer device 902 also includes one or more drive mechanisms 908 for interacting with any memory, such as a hard disk drive mechanism, an optical disc drive mechanism, etc.

[0139] The computer device 902 may also include an input / output interface 910 (I / O) for receiving various inputs (via the input device 912) and for providing various outputs (via the output device 914). A specific output mechanism may include a presentation device 916 and an associated graphical user interface 918 (GUI). In other embodiments, the input / output interface 910 (I / O), the input device 912, and the output device 914 may not be included, and it may only be a computer device in a network. The computer device 902 may also include one or more network interfaces 920 for exchanging data with other devices via one or more communication links 922. One or more communication buses 924 couple the components described above together.

[0140] The communication link 922 may be implemented in any way, for example, through a local area network, a wide area network (e.g., the Internet), a point-to-point connection, etc., or any combination thereof. The communication link 922 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc. governed by any protocol or combination of protocols.

[0141] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to some embodiments of the present specification. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processors to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processors produce a means for implementing the functions specified in one or more of the flows Figure 1 one or more of the flows and / or blocks Figure 1 or a means for implementing the functions specified in one or more of the blocks.

[0142] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processors to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction means that implements the functions specified in one or more of the flows Figure 1 one or more of the flows and / or blocks Figure 1 or a means for implementing the functions specified in one or more of the blocks.

[0143] These computer program instructions can also be loaded onto a computer or other programmable data processors, such that a series of operational steps are executed on the computer or other programmable device to generate a computer-implemented process, thereby providing steps for implementing the functions specified in one or more of the flows Figure 1 one or more of the flows and / or blocks Figure 1 or a means for implementing the functions specified in one or more of the blocks.

[0144] In a typical configuration, a computer device includes one or more processors (CPUs), an input / output interface, a network interface, and a memory.

[0145] The memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM), and / or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable media.

[0146] A computer-readable medium includes both permanent and non-permanent, removable and non-removable media that can store information by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transitory medium that can be used to store information accessible by a computing device. As defined in this specification, a computer-readable medium does not include transitory computer-readable media such as modulated data signals and carrier waves.

[0147] Those skilled in the art will understand that the embodiments of this specification can be provided as a method, a system, or a computer program product. Therefore, the embodiments of this specification can take the form of an all-hardware embodiment, an all-software embodiment, or an embodiment combining software and hardware aspects. Moreover, the embodiments of this specification can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0148] The embodiments of this specification can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The embodiments of this specification can also be practiced in a distributed computing environment where tasks are performed by remote processors connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0149] It should also be understood that in the embodiments of this specification, the term "and / or" is merely a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent three situations: A exists alone, both A and B exist simultaneously, and B exists alone. Additionally, the character " / " in this article generally represents an "or" relationship between the associated objects before and after.

[0150] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the differences between each embodiment and other embodiments are emphasized. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can refer to the description of the method embodiment.

[0151] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the embodiments of this specification. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0152] The above description is only for the embodiments of this application and is not intended to limit this application. For those skilled in the art, various changes and modifications can be made to this application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this application shall be included within the scope of the claims of this application.

Claims

1. A method for generating an underground parameter space based on formation constraints, characterized in that Including: Interpolating the work area based on the well location data and formation data of the known wells in the work area to obtain the formation distribution of the work area; Selecting a point to be predicted in the work area and determining the formation to which the point to be predicted belongs according to the formation distribution; Determining the vertical position of the point to be predicted in the formation; Determining the well sections of all the known wells located in the formation; Determining the vertical position corresponding to the point to be predicted in equal proportion in each of the well sections and taking this vertical position as the mapping point of the point to be predicted; the mapping point is the position point on the known well that is in the same formation as the point to be predicted and has a corresponding position; Determining the influence factor of the known well on the point to be predicted; Predicting the downhole parameters of the point to be predicted based on the downhole parameters of the mapping point and the influence factor; Predicting the downhole parameters of the remaining points to be predicted in the work area; Generating a downhole parameter distribution map of the work area according to the downhole parameters of each point to be predicted in the work area.

2. The method for generating the downhole parameter space based on formation constraints according to claim 1, wherein The determining the influence factor of the known well on the point to be predicted includes: Determining the influence factor of the known well on the point to be predicted according to the horizontal distance between the point to be predicted and the known well.

3. The downhole parameter space generation method based on formation constraint according to claim 1, wherein The interpolating the work area based on the well location data and formation data of the known wells in the work area includes: Uniformly dividing the work area into a network according to the coordinate range of the work area; Calculating the horizontal distance between the azimuth coordinates of all the known wells and the spatial grid points at each non-known well position respectively, and taking the reciprocal of each horizontal distance as the vertical depth influence weight of each known well on each spatial grid point; Calculating the total sum of the vertical depth influence weights of each spatial grid point; For the same formation boundary point of the known well, according to the formula Calculate the vertical depth of the same formation boundary at the spatial grid points; Among them, is the vertical depth of the same formation boundary at the spatial grid point, z i is the i-th same formation boundary point of the known well, d i is the distance between the i-th known well and the i-th spatial grid, Q i is the total vertical depth influence weight of the i-th spatial grid point, and n is the number of known wells.

4. The method for generating the downhole parameter space based on formation constraints according to claim 2, wherein The determining the influence factor of the known well on the point to be predicted according to the horizontal distance between the point to be predicted and the known well includes: According to the formula determine the influence factor of the known well on the point to be predicted; Among them, Z facter is the influence factor of the known well on the prediction point, d i is the distance between the i-th known well and the i-th spatial grid, Q i is the total vertical depth influence weight of the i-th spatial grid point, and n is the number of known wells.

5. The method for generating the downhole parameter space based on formation constraints according to claim 1, wherein, The predicting the downhole parameters of the point to be predicted based on the downhole parameters of the mapping point and the influence factor includes: Determining the product of the downhole parameters of each mapping point and the influence factor of the corresponding known well; Accumulating each of the products to obtain the downhole parameters of the point to be predicted.

6. The method for generating an underground parameter space based on formation constraints according to claim 1, characterized in that, After determining the downhole parameters of the remaining points to be predicted in the work area, it further includes: Generating a broken line graph of the downhole parameters of a specified area in the work area.

7. An underground parameter space generation device based on formation constraints, characterized in that, Including: An interpolation module for interpolating the work area based on the well location data and formation data of the known wells in the work area to obtain the formation distribution of the work area; A mapping module for selecting a point to be predicted in the work area and determining the formation to which the point to be predicted belongs according to the formation distribution; Determining the vertical position of the point to be predicted in the formation; Determining the well sections of all the known wells located in the formation; Determining the vertical position corresponding to the point to be predicted in equal proportion in each of the well sections and taking this vertical position as the mapping point of the point to be predicted; the mapping point is the position point on the known well that is in the same formation as the point to be predicted and has a corresponding position; A determining module for determining the influence factor of the known well on the point to be predicted; A prediction module, configured to predict the downhole parameters of the point to be predicted according to the downhole parameters of the mapping point and the influencing factor, and predict the downhole parameters of the remaining points to be predicted in the work area; A generation module, configured to generate a downhole parameter distribution map of the work area according to the downhole parameters of each point to be predicted in the work area.

8. A computer device, comprising a memory, a processor, and a computer program stored on the memory, characterized in that, When the computer program is run by the processor, it executes the instructions of the method according to any one of claims 1-6.

9. A computer storage medium, on which a computer program is stored, characterized in that, When the computer program is run by the processor of the computer device, it executes the instructions of the method according to any one of claims 1-6.

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