Method and device for determining production mode of shale gas well

Abstract

The application discloses a shale gas well production mode determination method and device, wherein the method comprises the following steps: obtaining geological data, field construction data and production data of a specified shale gas well; determining parameter values of multiple parameter items affecting the shale gas well production according to the data; inputting the parameter values of the multiple parameter items into a fuzzy comprehensive evaluation model, and determining grade information of the specified shale gas well by using the fuzzy comprehensive evaluation model; determining a production yield corresponding to the grade information of the specified shale gas well according to a preset corresponding relationship between shale gas well grade information and shale gas well production yield; and determining production mode information of the specified shale gas well according to the production yield corresponding to the grade information of the specified shale gas well. The application can quickly and accurately determine the production mode of the shale gas well, and avoid reducing the single well yield and the ultimate recoverable reserves of the shale gas well due to inappropriate production mode.

Description

Technical Field

[0001] This invention relates to the field of shale gas exploration and development technology, and in particular to a method and apparatus for determining the production mode of shale gas wells. Background Technology

[0002] This section is intended to provide background or context for the embodiments of the invention set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section.

[0003] Shale gas reservoirs have weak matrix permeability, and after volumetric fracturing, complex conductive fractures are formed. The significant difference in conductivity between the fractures and the matrix leads to a production pattern in shale gas wells: high initial production, rapid decline, and a long period of stable production in the later stages. Therefore, adopting appropriate production methods in the early stages of shale gas well development has a significant impact on the well's production and estimated ultimate recovery (EUR).

[0004] Currently, shale gas wells generally employ two production methods: high-yield production with pressure release and controlled-yield production. High-yield production with pressure release involves not restricting flow rate or production pressure at the wellhead, directly utilizing a large pressure differential in the initial production phase to achieve higher daily gas production. Controlled-yield production, on the other hand, typically involves setting up nozzles of different sizes at the wellhead to limit flow rate and slow the rate of pressure decline, sacrificing initial high production to achieve long-term stable production. In existing technologies, the selection of shale gas well production methods mainly relies on historical data and field trials for exploration and research. However, this approach is inefficient and prone to failing to properly select the optimal production method, potentially leading to a reduction in single-well production and ultimate recoverable reserves. Summary of the Invention

[0005] This invention provides a method for determining the production mode of a shale gas well, which can quickly and accurately determine the production mode of a shale gas well, improve the efficiency and accuracy of the determined shale gas well production mode, and avoid the reduction of single-well production and final recoverable reserves of shale gas wells due to inappropriate production modes. The method includes:

[0006] Obtain geological data, field construction data, and production data of a designated shale gas well; wherein the geological data is obtained through core sampling and laboratory evaluation experiments;

[0007] Based on geological data, field construction data, and production data, the parameter values ​​of several parameters that affect the production of shale gas wells are determined in advance. These parameters include matrix permeability, fracture conductivity, unsupported fracture stress sensitivity coefficient, fracturing fluid strength, average sand content of fracturing fluid, test production, and wellhead pressure.

[0008] Input the parameter values ​​of multiple parameters into a pre-built fuzzy comprehensive evaluation model, and use the fuzzy comprehensive evaluation model to determine the grade information of a specified shale gas well;

[0009] Based on the pre-defined correspondence between shale gas well grade information and shale gas well production output, determine the production output corresponding to the grade information of a specified shale gas well.

[0010] Based on the production output corresponding to the grade information of a specified shale gas well, the production method information of the specified shale gas well is determined. The production method information includes wellhead production allocation information, nozzle information for controlling production allocation, and wellhead pressure control data.

[0011] This invention also provides a device for determining the production mode of a shale gas well, used to quickly and accurately determine the production mode of a shale gas well, improving the efficiency and accuracy of the determined production mode, and avoiding a decrease in single-well production and final recoverable reserves due to inappropriate production modes. The device includes:

[0012] The data acquisition module is used to acquire geological data, on-site construction data, and production data of a specified shale gas well; wherein the geological data is acquired through core sampling and laboratory evaluation experiments.

[0013] The parameter value determination module is used to determine the parameter values ​​of multiple parameters that affect the production of shale gas wells based on geological data, field construction data, and production data. These multiple parameters include matrix permeability, fracture conductivity, unsupported fracture stress sensitivity coefficient, fracturing fluid strength, average sand content of fracturing fluid, test production, and wellhead pressure.

[0014] The grade determination module is used to input the parameter values ​​of multiple parameters into a pre-built fuzzy comprehensive evaluation model, and use the fuzzy comprehensive evaluation model to determine the grade information of a specified shale gas well.

[0015] The production determination module is used to determine the production output corresponding to the grade information of a specified shale gas well based on the preset correspondence between shale gas well grade information and shale gas well production output.

[0016] The production mode determination module is used to determine the production mode information of a specified shale gas well based on the production output corresponding to the grade information of the specified shale gas well. The production mode information includes wellhead production allocation information, nozzle information for controlling production allocation, and wellhead pressure control data.

[0017] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method for determining the production mode of the shale gas well described above.

[0018] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method for determining the production mode of a shale gas well.

[0019] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the method for determining the production mode of shale gas wells described above.

[0020] In this embodiment of the invention, geological data, field construction data, and production data of a designated shale gas well are acquired. The geological data is obtained through core sampling and laboratory evaluation experiments. Based on the geological data, field construction data, and production data, parameter values ​​for multiple parameters affecting shale gas well production are determined. These parameters include matrix permeability, fracture conductivity, unsupported fracture stress sensitivity coefficient, fracturing fluid strength, average sand content in the fracturing fluid, test production, and wellhead pressure. The parameter values ​​are input into a pre-constructed fuzzy comprehensive evaluation model, which is used to determine the grade information of the designated shale gas well. Based on the pre-defined correspondence between shale gas well grade information and shale gas well production output, the production output corresponding to the grade information of the designated shale gas well is determined. Based on the production output corresponding to the grade information of the designated shale gas well, the production method information of the designated shale gas well is determined, including wellhead production allocation information, nozzle information for controlling production allocation, and wellhead pressure control data. Compared to existing technologies that rely on historical data and field tests to determine shale gas well production methods, this invention utilizes a fuzzy comprehensive evaluation model to analyze several parameters of shale gas wells, including matrix permeability, fracture conductivity, unsupported fracture stress sensitivity coefficient, fracturing fluid strength, average sand content in the fracturing fluid, test production rate, and wellhead pressure. This analysis determines the well's grade information and, based on that, the optimal production rate is determined, allowing for a rapid and accurate selection of the production method. This approach enables the selection of the optimal production method for shale gas wells, preventing reductions in single-well production and final recoverable reserves due to inappropriate methods. Furthermore, it eliminates the need for sequential field tests based on historical data, improving the efficiency of shale gas well production method selection. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0022] Figure 1 This is a flowchart illustrating a method for determining the production mode of a shale gas well, as provided in an embodiment of the present invention.

[0023] Figure 2 This is a flowchart of a fuzzy comprehensive evaluation model construction method provided in an embodiment of the present invention;

[0024] Figure 3 This is a schematic diagram of a device for determining a shale gas well production method provided in an embodiment of the present invention;

[0025] Figure 4 This is a schematic diagram of a device for determining another shale gas well production method provided in an embodiment of the present invention;

[0026] Figure 5 This is a schematic diagram of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0028] In the description of this specification, the terms "comprising," "including," "having," and "containing" are open-ended terms, meaning that they include but are not limited to. The terms "an embodiment," "a specific embodiment," "some embodiments," and "for example," etc., refer to specific features, structures, or characteristics described in connection with that embodiment or example that are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, or characteristics described can be combined in any suitable manner in one or more embodiments or examples. The order of steps involved in the various embodiments is used to illustrate the implementation of this application, and the order of steps is not limited and can be adjusted appropriately as needed.

[0029] Research has found that in the early stages of shale gas well development, establishing a reasonable production method and adopting appropriate production allocation (i.e., configuring daily production output) can not only achieve a high gas production rate and quickly recover costs in the initial production phase, but also effectively protect the reservoir's conductivity and extend its stable production period through a mild pressure drop environment. Currently, the determination of shale gas well production methods mainly relies on historical data and field tests. However, due to the exceptionally dense nature of shale reservoirs and the more complex seepage patterns after fracturing, this approach is inefficient and prone to failing to properly select the optimal production method, potentially leading to a decrease in single-well production and ultimate recoverable reserves.

[0030] Therefore, this invention provides a scheme for determining the production method of shale gas wells. By comprehensively considering the reservoir characteristics, seepage patterns, and gas production capacity of shale gas wells, a more reasonable production method is established.

[0031] like Figure 1 The diagram shown is a flowchart of a method for determining the production mode of a shale gas well according to an embodiment of the present invention, which may include the following steps:

[0032] Step 101: Obtain geological data, field construction data, and production data for the specified shale gas well; wherein the geological data is obtained through core sampling and laboratory evaluation experiments;

[0033] Step 102: Based on geological data, field construction data, and production data, determine the parameter values ​​of several pre-set parameters that affect the production of shale gas wells; the multiple parameters include matrix permeability, fracture conductivity, unsupported fracture stress sensitivity coefficient, fracturing fluid strength, average sand content of fracturing fluid, test production, and wellhead pressure.

[0034] Step 103: Input the parameter values ​​of multiple parameter items into the pre-constructed fuzzy comprehensive evaluation model, and use the fuzzy comprehensive evaluation model to determine the grade information of the specified shale gas well;

[0035] Step 104: Determine the production output corresponding to the grade information of a specified shale gas well based on the preset correspondence between shale gas well grade information and shale gas well production output.

[0036] Step 105: Determine the production method information of the designated shale gas well based on the production output corresponding to the grade information of the designated shale gas well. The production method information includes wellhead production allocation information, nozzle information for controlling production allocation, and wellhead pressure control data.

[0037] In this embodiment of the invention, geological data, field construction data, and production data of a designated shale gas well are acquired. The geological data is obtained through core sampling and laboratory evaluation experiments. Based on the geological data, field construction data, and production data, parameter values ​​for multiple parameters affecting shale gas well production are determined. These parameters include matrix permeability, fracture conductivity, unsupported fracture stress sensitivity coefficient, fracturing fluid strength, average sand content in the fracturing fluid, test production, and wellhead pressure. The parameter values ​​are input into a pre-constructed fuzzy comprehensive evaluation model, which is used to determine the grade information of the designated shale gas well. Based on the pre-defined correspondence between shale gas well grade information and shale gas well production output, the production output corresponding to the grade information of the designated shale gas well is determined. Based on the production output corresponding to the grade information of the designated shale gas well, the production method information of the designated shale gas well is determined, including wellhead production allocation information, nozzle information for controlling production allocation, and wellhead pressure control data. Compared to existing technologies that rely on historical data and field tests to determine shale gas well production methods, this invention utilizes a fuzzy comprehensive evaluation model to analyze several parameters of shale gas wells, including matrix permeability, fracture conductivity, unsupported fracture stress sensitivity coefficient, fracturing fluid strength, average sand content in the fracturing fluid, test production rate, and wellhead pressure. This analysis determines the well's grade information and, based on that, the optimal production rate is determined, allowing for a rapid and accurate selection of the production method. This approach enables the selection of the optimal production method for shale gas wells, preventing reductions in single-well production and final recoverable reserves due to inappropriate methods. Furthermore, it eliminates the need for sequential field tests based on historical data, improving the efficiency of shale gas well production method selection.

[0038] In this embodiment of the invention, a comprehensive analysis of the reservoir characteristics, seepage patterns, and gas production capacity of shale gas wells is conducted, analyzing them from three aspects: geological factors, engineering factors, and production factors, to pre-determine multiple parameters affecting the production of shale gas wells. Geological factors may include: matrix permeability, fracture conductivity, and unsupported fracture stress sensitivity coefficient; engineering factors may include: fracturing fluid strength and average sand content in the fracturing fluid; and production factors may include: test production rate and wellhead pressure.

[0039] Specifically, the matrix permeability mentioned above is an important indicator reflecting the gas flow capacity within the reservoir; fracture conductivity reflects the flow capacity of fractures after reservoir fracturing; unsupported fracture stress sensitivity coefficient measures the sensitivity of unsupported fracture conductivity to stress changes; fracturing fluid strength reflects the size of the fracturing volume and the complexity of the fracture network; average sand content of fracturing fluid reflects the storage space and flow capacity of the fracturing propped fractures; test production is an important indicator reflecting the initial production of the gas well; and wellhead pressure is an important indicator reflecting the reservoir pressure.

[0040] The following is about Figure 1 The method for determining the production mode of the shale gas wells shown is explained in detail.

[0041] In step 101 above, geological data, on-site construction data, and production data of a specified shale gas well can be obtained.

[0042] In practice, geological data can be obtained through core sampling and indoor evaluation experiments.

[0043] In step 102 above, the parameter values ​​of the above-mentioned multiple parameter items are determined based on the geological data, on-site construction data and production data obtained in step 101.

[0044] In this embodiment of the invention, parameter values ​​for multiple parameters are determined based on geological data, on-site construction data, and production data. Specifically, this may include:

[0045] Based on geological data, determine the parameter values ​​corresponding to matrix permeability, fracture conductivity, and stress sensitivity coefficient of unsupported fractures.

[0046] Based on the on-site construction data, determine the parameter values ​​corresponding to the fracturing fluid strength and the average sand content of the fracturing fluid, respectively.

[0047] Based on the production data, determine the parameter values ​​corresponding to the test output and wellhead pressure, respectively.

[0048] In step 103 above, the parameter values ​​of multiple parameter items can be input into a pre-constructed fuzzy comprehensive evaluation model, and the fuzzy comprehensive evaluation model can be used to determine the grade information of a specified shale gas well.

[0049] Among them, the fuzzy comprehensive evaluation model is a comprehensive evaluation method in fuzzy mathematics. Specifically, when evaluating a certain matter, we often encounter a problem where the evaluation of a matter is determined by multiple factors, so each factor needs to be evaluated. Based on making a separate evaluation for each factor, how to consider all factors and make a comprehensive evaluation is a comprehensive evaluation problem.

[0050] In this embodiment of the invention, a fuzzy comprehensive evaluation model is used to comprehensively evaluate the parameter values ​​of multiple parameters affecting the production of shale gas wells, thereby achieving the grade assessment (or quality level) of shale gas wells.

[0051] The construction of the fuzzy comprehensive evaluation model in this embodiment of the invention mainly includes establishing a hierarchical structure model, constructing a judgment matrix, solving for weight values, and verifying the rationality of the weights. For example... Figure 2 As shown, the fuzzy comprehensive evaluation model can be constructed using the following method:

[0052] Step 201: For multiple parameter items, set the level classification information and the scale of each parameter item; the scale of each parameter item is used to indicate the weight information of the parameter item relative to other parameter items among the multiple parameter items; the level classification information of each parameter item includes the level information to which different parameter values ​​of each parameter item belong.

[0053] Step 202: Determine the weight value of each parameter item based on the analytic hierarchy process and the scale of each parameter item;

[0054] Step 203: Construct a fuzzy comprehensive evaluation model based on the grade classification information of each parameter item and the weight value of each parameter item.

[0055] In practical implementation, step 201 above is the step of establishing a hierarchical structure model: it is necessary to set the level classification information for each parameter item for multiple parameter items, that is, the classification standard of single-parameter evaluation index; wherein, the level classification information of each parameter item includes the level information to which different parameter values ​​of each parameter item belong. For example, the level classification information of each parameter item can be as shown in Table 1.

[0056] Table 1. Parameter Item Classification Information

[0057]

[0058] In step 201 above, it is also necessary to set the scale for each parameter item. The scale for each parameter item is used to indicate the weight of the parameter item relative to the other parameter items among the multiple parameter items.

[0059] In practice, different scales represent different degrees of importance between two factors (i.e., two parameter items). To quantify the comparison of two factors, the 1-9 ratio scale method is introduced, and the different scales and their meanings are shown in Table 2.

[0060] Table 2. Scales and their meanings

[0061] Scale meaning 1 This indicates that the two factors are equally important. 3 This indicates that one factor is slightly more important than the other. 5 This indicates that one factor is significantly more important than the other when comparing two factors. 7 This indicates that one factor is significantly more important than the other when comparing two factors. 9 This indicates that one factor is more important than the other. 2，4 The median of the above adjacent judgments 6，8 The median of the above adjacent judgments reciprocal <![CDATA[When factor i is compared with factor j to obtain judgment b ij , then when factor j is compared with factor i, judgment b ji = 1 / b ij >

[0062] In this embodiment of the invention, the influence of multiple parameters on shale gas well production can be analyzed. According to the scale and its meaning shown in Table 2, the scale of each parameter can be set. Specifically, the scale of each parameter can be as shown in Table 3.

[0063] Table 3 Scale of Parameter Items

[0064] Parameters Meaning and nature Scale Matrix permeability An important indicator reflecting the gas flow capacity within a reservoir. 1 Average sand content of fracturing fluid Reflects the reservoir space and flow capacity of the fracturing propped joint. 2 Crack conductivity Reflects the flow capacity of fractures after reservoir fracturing. 2 Unsupported crack stress sensitivity coefficient Assessing the sensitivity of unsupported crack conductivity to stress changes 3 fracturing fluid strength Reflects the size of the fracturing volume and the complexity of the fracture network 4 Wellhead pressure An important indicator reflecting reservoir pressure 4 Test yield An important indicator reflecting the initial production of gas wells 4

[0065] In practice, in step 202 above, the weight value of each parameter item is determined according to the analytic hierarchy process and the scale of each parameter item.

[0066] It should be noted that the Analytic Hierarchy Process (AHP) refers to decomposing a problem into components at different levels based on its nature and overall direction. Then, according to the interrelationships and hierarchical relationships between these components, the components are combined hierarchically to form a structural model at different levels. This hierarchical approach allows for the systematic ranking or weighting of the problem from the bottom to the top.

[0067] In this embodiment of the invention, step 202 may specifically include:

[0068] A judgment matrix is ​​constructed based on the scale of each parameter item; the judgment matrix is ​​used to represent the weight information of pairwise comparisons of each parameter item;

[0069] Calculate the weight value of each parameter item based on the judgment matrix and the hierarchical analysis method;

[0070] Perform a consistency check on the weight value of each parameter item; if the check passes, it means that the weight value of each parameter item is correct.

[0071] In practice, based on the scale of each parameter item shown in Table 3, multiple parameter items are compared pairwise to obtain the results shown in Table 4.

[0072] Table 4 Comparison Results of Parameter Items

[0073]

[0074] Then, based on the comparison results in Table 4, a judgment matrix A can be constructed:

[0075]

[0076] In practice, the weight value of each parameter item is calculated based on the judgment matrix A and the analytic hierarchy process (AHP). This may include the following steps:

[0077] (1) Calculate the product M of the elements in the i-th row of the judgment matrix. i ;

[0078] (2) Calculate Mi nth root

[0079] (3) According to Formula 1 below, for vector After normalization, the weights w are obtained. i Thus, the weight set is obtained;

[0080]

[0081] (4) Calculate the largest eigenvalue λ of the judgment matrix. max ;

[0082] (5) Calculate the consistency index CI for judging matrix deviation according to the following formula 2;

[0083]

[0084] (6) Calculate the random consistency ratio CR of the judgment matrix according to the following formula 3.

[0085] CR = CI / RI (Formula 3)

[0086] In the above formulas 1, 2, and 3:

[0087] CI is a consistency indicator; λ max The largest eigenvalue of the judgment matrix is ​​denoted by n; n is the number of judgment factors; CR is the random consistency ratio, and when CR < 0.10, the consistency is satisfactory; RI is the average random consistency ratio (as shown in Table 5).

[0088] If the consistency requirement is met, then the weight set W = (w1, w2, ..., w n If the calculation is reasonable, then adjust the judgment matrix and recalculate.

[0089] Table 5 Average Random Consistency Ratio

[0090] Number of factors 1 2 3 4 5 6 7 8 9 RI value 0.00 0.00 0.58 0.90 1.12 1.24 1.32 1.41 1.45

[0091] In this embodiment of the invention, the set of weight values ​​for the parameter items obtained according to the above method is {0.050, 0.100, 0.100, 0.150, 0.200, 0.200, 0.200}. That is, the weight of matrix permeability is 0.05, the weight of average sand content of fracturing fluid is 0.1, the weight of fracture conductivity is 0.1, the weight of unsupported fracture stress sensitivity coefficient is 0.15, the weight of fracturing fluid usage is 0.2, the weight of wellhead pressure is 0.2, and the weight of test production is 0.2.

[0092] In this way, the process of subjective thinking can be mathematically objectified according to the Analytic Hierarchy Process (AHP), thereby effectively performing quantitative analysis of the importance of each parameter while qualitatively analyzing complex problems.

[0093] In step 203 above, a fuzzy comprehensive evaluation model is constructed based on the level classification information of each parameter item and the weight value of each parameter item.

[0094] In specific implementation, step 203 may include:

[0095] The fuzzy comprehensive evaluation model is constructed according to the following formula 4:

[0096] y = x × P T Formula 4

[0097] Where y represents the shale gas well grade information; x represents the weight matrix corresponding to the weight values ​​of multiple parameter terms; P T This represents the level transformation matrix of parameter values ​​for multiple parameter items, determined based on the level classification information of each parameter item.

[0098] For example, x can be: x = [0.050, 0.100, 0.100, 0.150, 0.200, 0.200, 0.200];

[0099] P T It could be: calculate the membership degree of the level information to which the parameter value of each parameter item belongs based on the level classification information of each parameter item, and then determine the level transformation matrix of the parameter values ​​of multiple parameter items based on the membership degree of the level information to which the parameter value of each parameter item belongs.

[0100] In summary, in this embodiment of the invention, the grade information of a specified shale gas well can be calculated based on the parameter values ​​of multiple parameter items obtained in step 102 and the above formula 4. This grade information can be expressed in the form of a score.

[0101] In step 104 above, the production output corresponding to the grade information of a specified shale gas well can be determined based on the pre-set correspondence between the shale gas well grade information and the shale gas well production output.

[0102] In practice, the correspondence between shale gas well grade information and shale gas well production output can be shown in Table 6. If the grade information (comprehensive score) of a specified shale gas well falls within the range of "Class I" shale gas wells, then the specified shale gas well belongs to Class I wells, and the reasonable production allocation (production output) for the first year can be determined to be 200,000 cubic meters per day.

[0103] Table 6. Correspondence between shale gas well grade information and shale gas well production output.

[0104] Shale gas well categories A type Category II Three categories Category Four Overall score 1～0.75 0.60～0.75 0.45～0.6 <0.45 Production / 10,000 cubic meters / day 20 15 10 5

[0105] In step 105 above, after determining the production output corresponding to the grade information of a specified shale gas well, the production method information of the specified shale gas well can be determined based on the production output corresponding to the grade information. This production method information may include wellhead production allocation information, nozzle information for controlling production allocation, and wellhead pressure control data.

[0106] In other words, if the daily production output of a shale gas well is limited to 200,000 cubic meters per day, it is necessary to control the production output and wellhead pressure of the shale gas well through reasonable means (using different nozzle sizes). Therefore, the wellhead production allocation information, nozzle information for controlling production allocation, and wellhead pressure control data of a specified shale gas well can be determined based on the production output corresponding to the grade information of the specified shale gas well.

[0107] The following specific example illustrates the method for determining the production mode of shale gas wells as described above.

[0108] 1. Based on the obtained geological data, on-site construction data, and production data of the shale gas wells, the parameter values ​​for several parameters affecting shale gas well production were determined as follows:

[0109] The matrix permeability X1 is 0.0005 mD, the fracture conductivity X2 is 80 mD·m, and the stress sensitivity coefficient of the unsupported fracture X3 is 0.045 MPa. -1 The fracturing fluid strength Y1 is 38m. 3 / m, average fracturing fluid sand content Y2 is 2.1t / m, test production Z1 is 450,000 cubic meters / day, and wellhead pressure Z2 is 32MPa.

[0110] 2. Based on the fuzzy comprehensive evaluation model already constructed above, X1: 0.0005mD, X2: 80mD.m, X3: 0.045MPa -1 Y1: 38m 3 / m, Y2: 2.1t / m, Z1: 450,000 cubic meters / day, Z2: 32MPa, substituting into Formula 4, we get:

[0111] y = x × P T ;

[0112] in

[0113]

[0114] The combined score of the shale gas wells, calculated by adding the results of the individual index evaluations, is 0.752.

[0115] Then, according to Table 6, the shale gas well category corresponding to a comprehensive score of 0.752 is Class I, and the corresponding production data is 200,000 cubic meters / day.

[0116] 3. Based on the production data of 200,000 cubic meters per day, the production method information of this shale gas well can be obtained.

[0117] In this embodiment of the invention, in conjunction with special experiments, not only the reservoir space parameters of shale gas wells are considered, but also the flow capacity parameters; based on the statistical analysis results, a classification standard for single evaluation parameters is established; the comprehensive scoring of parameters is calculated using the model to comprehensively reflect the micro-mobility capacity of the reservoir; the evaluation results can provide support for drilling target layers and the selection of sweet spots for development.

[0118] This invention also provides a device for determining the production mode of a shale gas well, as described in the following embodiments. Since the principle by which this device solves the problem is similar to the method for determining the production mode of a shale gas well, the implementation of this device can refer to the implementation of the method for determining the production mode of a shale gas well, and will not be repeated here.

[0119] like Figure 3 The diagram shown is a schematic of a device for determining a shale gas well production method according to an embodiment of the present invention. The device may include:

[0120] The data acquisition module 301 is used to acquire geological data, on-site construction data, and production data of a specified shale gas well; wherein the geological data is acquired through core sampling and laboratory evaluation experiments.

[0121] The parameter value determination module 302 is used to determine the parameter values ​​of multiple parameters that affect the production of shale gas wells based on geological data, field construction data, and production data. The multiple parameters include matrix permeability, fracture conductivity, unsupported fracture stress sensitivity coefficient, fracturing fluid strength, average sand content of fracturing fluid, test production, and wellhead pressure.

[0122] The grade determination module 303 is used to input the parameter values ​​of multiple parameter items into a pre-constructed fuzzy comprehensive evaluation model, and use the fuzzy comprehensive evaluation model to determine the grade information of a specified shale gas well.

[0123] The production determination module 304 is used to determine the production output corresponding to the grade information of a specified shale gas well based on the preset correspondence between shale gas well grade information and shale gas well production output.

[0124] The production mode determination module 305 is used to determine the production mode information of a specified shale gas well based on the production output corresponding to the grade information of the specified shale gas well. The production mode information includes wellhead production allocation information, nozzle information for controlling production allocation, and wellhead pressure control data.

[0125] In this embodiment of the invention, the parameter value determination module 302 can be specifically used for:

[0126] Based on geological data, determine the parameter values ​​corresponding to matrix permeability, fracture conductivity, and stress sensitivity coefficient of unsupported fractures.

[0127] Based on the on-site construction data, determine the parameter values ​​corresponding to the fracturing fluid strength and the average sand content of the fracturing fluid, respectively.

[0128] Based on the production data, determine the parameter values ​​corresponding to the test output and wellhead pressure, respectively.

[0129] In embodiments of the present invention, such as Figure 4 As shown, it may also include a model building module 401, used before the level determination module 303 inputs the parameter values ​​of multiple parameter items into the pre-built fuzzy comprehensive evaluation model and uses the fuzzy comprehensive evaluation model to determine the level information of a specified shale gas well:

[0130] The fuzzy comprehensive evaluation model can be constructed using the following method:

[0131] For multiple parameter items, a grading information and a scale are set for each parameter item; the scale of each parameter item is used to indicate the weight of the parameter item relative to other parameter items among the multiple parameter items; the grading information of each parameter item includes the grading information to which different parameter values ​​of each parameter item belong.

[0132] Based on the analytic hierarchy process and the scaling of each parameter item, determine the weight value of each parameter item;

[0133] A fuzzy comprehensive evaluation model is constructed based on the level classification information and weight value of each parameter item.

[0134] In this embodiment of the invention, the model building module can also be used for:

[0135] A judgment matrix is ​​constructed based on the scale of each parameter item; the judgment matrix is ​​used to represent the weight information of pairwise comparisons of each parameter item;

[0136] Calculate the weight value of each parameter item based on the judgment matrix and the hierarchical analysis method;

[0137] Perform a consistency check on the weight value of each parameter item; if the check passes, it means that the weight value of each parameter item is correct.

[0138] In this embodiment of the invention, the model building module can also be used for:

[0139] The fuzzy comprehensive evaluation model is constructed using the following formula:

[0140] y = x × P T

[0141] Where y represents the shale gas well grade information; x represents the weight matrix corresponding to the weight values ​​of multiple parameter terms; P T This represents the level transformation matrix of parameter values ​​for multiple parameter items, determined based on the level classification information of each parameter item.

[0142] This invention also provides a computer device, such as... Figure 5 The diagram shown is a schematic of a computer device in an embodiment of the present invention. The computer device 500 includes a memory 510, a processor 520, and a computer program 530 stored in the memory 510 and executable on the processor 520. When the processor 520 executes the computer program 530, it implements the method for determining the production mode of the shale gas well described above.

[0143] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method for determining the production mode of a shale gas well.

[0144] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the method for determining the production mode of shale gas wells described above.

[0145] In this embodiment of the invention, geological data, field construction data, and production data of a designated shale gas well are acquired. The geological data is obtained through core sampling and laboratory evaluation experiments. Based on the geological data, field construction data, and production data, parameter values ​​for multiple parameters affecting shale gas well production are determined. These parameters include matrix permeability, fracture conductivity, unsupported fracture stress sensitivity coefficient, fracturing fluid strength, average sand content in the fracturing fluid, test production, and wellhead pressure. The parameter values ​​are input into a pre-constructed fuzzy comprehensive evaluation model, which is used to determine the grade information of the designated shale gas well. Based on the pre-defined correspondence between shale gas well grade information and shale gas well production output, the production output corresponding to the grade information of the designated shale gas well is determined. Based on the production output corresponding to the grade information of the designated shale gas well, the production method information of the designated shale gas well is determined, including wellhead production allocation information, nozzle information for controlling production allocation, and wellhead pressure control data. Compared to existing technologies that rely on historical data and field tests to determine shale gas well production methods, this invention utilizes a fuzzy comprehensive evaluation model to analyze several parameters of shale gas wells, including matrix permeability, fracture conductivity, unsupported fracture stress sensitivity coefficient, fracturing fluid strength, average sand content, test production rate, and wellhead pressure. This analysis determines the well's grade information and, based on that, the optimal production rate. Consequently, the optimal production method for shale gas wells can be determined quickly and accurately. This allows for the selection of the best production method, preventing reductions in single-well production and final recoverable reserves due to inappropriate methods. Furthermore, it eliminates the need for sequential field tests based on historical data, improving the efficiency of shale gas well production method selection.

[0146] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0147] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0148] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0149] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0150] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for determining the production mode of a shale gas well, characterized in that, include: Obtain geological data, field construction data, and production data of a designated shale gas well; wherein the geological data is obtained through core sampling and laboratory evaluation experiments; Based on geological data, field construction data, and production data, the parameter values ​​of several parameters that affect the production of shale gas wells are determined in advance. These parameters include matrix permeability, fracture conductivity, unsupported fracture stress sensitivity coefficient, fracturing fluid strength, average sand content of fracturing fluid, test production, and wellhead pressure. Input the parameter values ​​of multiple parameters into a pre-built fuzzy comprehensive evaluation model, and use the fuzzy comprehensive evaluation model to determine the grade information of a specified shale gas well; Based on the pre-defined correspondence between shale gas well grade information and shale gas well production output, determine the production output corresponding to the grade information of a specified shale gas well. Based on the production output corresponding to the grade information of a specified shale gas well, the production method information of the specified shale gas well is determined. The production method information includes wellhead production allocation information, nozzle information for controlling production allocation, and wellhead pressure control data. Before inputting the parameter values ​​of multiple parameters into a pre-constructed fuzzy comprehensive evaluation model and using the fuzzy comprehensive evaluation model to determine the grade information of a specified shale gas well, the following steps are also included: A fuzzy comprehensive evaluation model is constructed as follows: For multiple parameter items, a rank classification information and a scale are set for each parameter item; the scale of each parameter item is used to indicate the weight information of that parameter item relative to other parameter items among the multiple parameter items; the rank classification information of each parameter item includes the rank information to which different parameter values ​​of each parameter item belong; the weight value of each parameter item is determined according to the analytic hierarchy process and the scale of each parameter item; and a fuzzy comprehensive evaluation model is constructed based on the rank classification information and the weight value of each parameter item. The weight value of each parameter item is determined based on the analytic hierarchy process (AHP) and the scaling of each parameter item, including: constructing a judgment matrix based on the scaling of each parameter item; the judgment matrix is ​​used to represent the weight information of each parameter item in pairwise comparisons; calculating the weight value of each parameter item based on the judgment matrix and the AHP; performing a consistency check on the weight value of each parameter item; if the check passes, it indicates that the weight value of each parameter item is correct.

2. The method as described in claim 1, characterized in that, Based on geological data, on-site construction data, and production data, parameter values ​​for several pre-defined parameters affecting shale gas well production were determined, including: Based on geological data, determine the parameter values ​​corresponding to matrix permeability, fracture conductivity, and stress sensitivity coefficient of unsupported fractures. Based on the on-site construction data, determine the parameter values ​​corresponding to the fracturing fluid strength and the average sand content of the fracturing fluid, respectively. Based on the production data, determine the parameter values ​​corresponding to the test output and wellhead pressure, respectively.

3. The method as described in claim 1, characterized in that, Based on the level classification information and weight value of each parameter item, a fuzzy comprehensive evaluation model is constructed, including: The fuzzy comprehensive evaluation model is constructed using the following formula: Where y represents the grade information of the shale gas well; P represents the weight matrix corresponding to the weight values ​​of multiple parameter terms. T This represents the level transformation matrix of parameter values ​​for multiple parameter items, determined based on the level classification information of each parameter item.

4. A device for determining the production mode of a shale gas well, characterized in that, include: The data acquisition module is used to acquire geological data, on-site construction data, and production data of a specified shale gas well; wherein the geological data is acquired through core sampling and laboratory evaluation experiments. The parameter value determination module is used to determine the parameter values ​​of multiple parameters that affect the production of shale gas wells based on geological data, field construction data, and production data. These multiple parameters include matrix permeability, fracture conductivity, unsupported fracture stress sensitivity coefficient, fracturing fluid strength, average sand content of fracturing fluid, test production, and wellhead pressure. The grade determination module is used to input the parameter values ​​of multiple parameters into a pre-built fuzzy comprehensive evaluation model, and use the fuzzy comprehensive evaluation model to determine the grade information of a specified shale gas well. The production determination module is used to determine the production output corresponding to the grade information of a specified shale gas well based on the preset correspondence between shale gas well grade information and shale gas well production output. The production method determination module is used to determine the production method information of a specified shale gas well based on the production output corresponding to the grade information of the specified shale gas well. The production method information includes wellhead production allocation information, nozzle information for controlling production allocation, and wellhead pressure control data. It also includes a model building module, used before the grading module inputs the parameter values ​​of multiple parameter items into a pre-built fuzzy comprehensive evaluation model, and uses the fuzzy comprehensive evaluation model to determine the grading information of a specified shale gas well: A fuzzy comprehensive evaluation model is constructed as follows: For multiple parameter items, a rank classification information and a scale are set for each parameter item; the scale of each parameter item is used to indicate the weight information of that parameter item relative to other parameter items among the multiple parameter items; the rank classification information of each parameter item includes the rank information to which different parameter values ​​of each parameter item belong; the weight value of each parameter item is determined according to the analytic hierarchy process and the scale of each parameter item; and a fuzzy comprehensive evaluation model is constructed based on the rank classification information and the weight value of each parameter item. The model building module is also used to: construct a judgment matrix based on the scale of each parameter item; the judgment matrix is ​​used to represent the weight information of each parameter item in pairwise comparisons; calculate the weight value of each parameter item based on the judgment matrix and the analytic hierarchy process; perform consistency verification on the weight value of each parameter item; if the verification passes, it indicates that the weight value of each parameter item is correct.

5. The apparatus as described in claim 4, characterized in that, The parameter value determination module is specifically used for: Based on geological data, determine the parameter values ​​corresponding to matrix permeability, fracture conductivity, and stress sensitivity coefficient of unsupported fractures. Based on the on-site construction data, determine the parameter values ​​corresponding to the fracturing fluid strength and the average sand content of the fracturing fluid, respectively. Based on the production data, determine the parameter values ​​corresponding to the test output and wellhead pressure, respectively.

6. The apparatus as claimed in claim 4, characterized in that, The model building module is also used for: The fuzzy comprehensive evaluation model is constructed using the following formula: Where y represents the grade information of the shale gas well; P represents the weight matrix corresponding to the weight values ​​of multiple parameter terms. T This represents the level transformation matrix of parameter values ​​for multiple parameter items, determined based on the level classification information of each parameter item.

7. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 3.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 3.

9. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 3.

Images