Construction method and device of fracture control oil and gas accumulation prediction model

Abstract

The invention provides a method and device for constructing a fracture control oil and gas reservoir forming prediction model, and the method comprises the steps: calculating a well reservoir distance between a target oil and gas well position in a target region and a reservoir control fracture position corresponding to the target oil and gas well position, according to a preset distance interval, dividing an oil and gas accumulation interval determined based on the minimum well reservoir distance and the maximum well reservoir distance into a plurality of distance intervals; the oil and gas well production performance value corresponding to each distance interval is calculated, and the reservoir forming probability of the distance interval corresponding to the maximum production performance value serves as the reference reservoir forming probability; and calculating the reservoir forming probability corresponding to each distance interval according to the reference reservoir forming probability and the oil and gas production performance value corresponding to each distance interval, and constructing a reservoir forming prediction model according to each distance interval and the reservoir forming probability corresponding to the distance interval. On the basis of the fracture distance and oil and gas well related information, key parameters are digitalized, a reservoir forming prediction model between the reservoir forming probability and the fracture distance is established, and then the fracture oil and gas control effect is quantitatively represented.

Description

Technical Field

[0001] This invention relates to the field of oil and gas geology, and in particular to a method and apparatus for constructing a fracture-controlled oil and gas accumulation prediction model. Background Technology

[0002] Faults, as a common geological phenomenon in the Earth's crust, play a significant role in controlling the generation, migration, and accumulation of hydrocarbons. They not only affect the distribution and accumulation of hydrocarbon reservoirs but also directly impact the success rate of oil and gas exploration and development. Therefore, quantitatively evaluating the controlling effect of faults on hydrocarbon accumulation is of great importance for oil and gas exploration and development.

[0003] The prior art CN114118773A discloses an evaluation method for fault-controlled oil and gas enrichment, which guides oil and gas exploration by taking into account the oil supply capacity, conduction capacity, and charging capacity of the target fault. However, the prior art is a qualitative understanding and theoretical result, and it is difficult to quantitatively characterize the effect of faults on oil and gas enrichment, which has significant limitations in practical applications. Summary of the Invention

[0004] Therefore, it is necessary to provide a method and apparatus for constructing a fracture-controlled hydrocarbon accumulation prediction model to address the aforementioned technical problems.

[0005] A method for constructing a fracture-controlled hydrocarbon accumulation prediction model includes:

[0006] Obtain the location of each target oil and gas well in the target area and the location of the reservoir-controlling fracture corresponding to each target oil and gas well location;

[0007] Calculate the well-reservoir distance between the locations of each target oil and gas well and the locations of the reservoir-controlling faults corresponding to each target oil and gas well location, determine the oil and gas reservoir formation interval based on the minimum and maximum well-reservoir distances, and divide the oil and gas reservoir formation interval into multiple distance intervals according to a preset distance interval;

[0008] Calculate the oil and gas well production performance value corresponding to each distance interval, and take the oil reservoir formation probability of the distance interval corresponding to the largest production performance value as the benchmark oil reservoir formation probability;

[0009] The probability of hydrocarbon accumulation for each distance interval is calculated based on the baseline hydrocarbon accumulation probability and the oil and gas production performance value corresponding to each distance interval. A hydrocarbon accumulation prediction model is constructed based on each distance interval and the hydrocarbon accumulation probability corresponding to each distance interval. The hydrocarbon accumulation prediction model is used to predict the hydrocarbon accumulation probability distribution characteristics of the target area.

[0010] In one embodiment, calculating the accumulation probability corresponding to each distance interval based on the baseline accumulation probability and the corresponding oil and gas production performance values ​​of each distance interval includes:

[0011] The maximum production performance value is used as the benchmark production performance value to obtain the production performance value corresponding to each distance interval.

[0012] For each distance interval, the ratio of the production performance value corresponding to the distance interval to the benchmark production performance value is calculated. Based on the ratio and the benchmark oil and gas accumulation probability, the oil and gas accumulation probability corresponding to the distance interval is calculated.

[0013] In one embodiment, obtaining the locations of each target oil and gas well in the target area and the locations of the reservoir-controlling fractures corresponding to each target oil and gas well location includes:

[0014] Determine the oil and gas well data and the reservoir-controlling fracture data corresponding to each oil and gas well in the target area. The oil and gas well data includes the location and production of the oil and gas wells, and the reservoir-controlling fracture data includes the degree and location of the fractures.

[0015] The system detects whether the production of each oil and gas well has reached the preset production rate. When the production of the oil and gas well reaches the preset production rate, the location of the oil and gas well corresponding to the production rate is determined as the target oil and gas well location.

[0016] The degree of fracture of each controlled reservoir is detected to see if it reaches the preset degree of fracture. When the degree of fracture reaches the preset degree of fracture, the fracture position corresponding to the degree of fracture is determined as the target controlled reservoir fracture position.

[0017] In one embodiment, after constructing an oil and gas accumulation prediction model based on the distance interval and the corresponding probability of oil and gas accumulation, the method further includes:

[0018] Obtain the verification locations of oil and gas wells in the target area, and the verification locations of reservoir-controlling fractures corresponding to the verification locations of the oil and gas wells;

[0019] Determine the distance difference between the verification location of the oil and gas well and the verification location of the reservoir-controlling fracture, the verification value of the oil and gas well production performance corresponding to the distance difference, and the total production performance value of the oil and gas wells in the target area;

[0020] The distance difference is input into the hydrocarbon accumulation prediction model, and the distance difference is processed by the hydrocarbon accumulation prediction model to obtain the predicted distance interval corresponding to the distance difference and the hydrocarbon accumulation probability in the predicted distance interval;

[0021] Based on the hydrocarbon accumulation verification probability and the total production performance value, the predicted production performance value corresponding to the predicted distance interval is calculated.

[0022] The difference between the predicted production performance value and the verified production performance value of the oil and gas well is checked to see if it is within a preset difference range.

[0023] When the difference between the predicted production performance value and the verified production performance value of the oil and gas well is within the preset difference range, the reservoir formation prediction model is determined.

[0024] In one embodiment, the production performance value is the number of oil and gas wells or the daily cumulative production capacity of oil and gas wells.

[0025] In one embodiment, the expression of the hydrocarbon accumulation prediction model is:

[0026] P f =We Rl

[0027] Among them, P f Let P be the probability of hydrocarbon accumulation, 0 ≤ P f ≤1; l is the coefficient related to the two endpoints of the distance interval where the well reservoir is located; e is a constant coefficient, R is a constant, and W is the coefficient relating the reservoir formation probability to the distance interval.

[0028] In one embodiment, the coefficient related to the two endpoints of the distance interval containing the well reservoir distance is the average of the two endpoints of the distance interval containing the well reservoir distance.

[0029] In one embodiment, after constructing an oil and gas accumulation prediction model based on each distance interval and the corresponding probability of oil and gas accumulation for each distance interval, the method further includes:

[0030] The distance of the reservoir-controlling fault to be measured in the target area is obtained, and the distance of the reservoir-controlling fault to be measured is input into the reservoir formation prediction model. The reservoir formation prediction model is used to calculate the distance of the reservoir-controlling fault to be measured, and the probability of reservoir formation in the distance interval corresponding to the distance of the reservoir-controlling fault to be measured is obtained.

[0031] Determine the basic contour image of the target area, and combine the basic contour image with the hydrocarbon accumulation probability to generate a fault-controlled hydrocarbon accumulation probability distribution image.

[0032] An apparatus for constructing a fracture-controlled hydrocarbon accumulation prediction model, comprising:

[0033] The acquisition module is used to acquire the location of each target oil and gas well in the target area and the location of the reservoir-controlling fracture corresponding to each target oil and gas well location;

[0034] The division module is used to calculate the well-reservoir distance between the locations of each target oil and gas well and the locations of the reservoir-controlling faults corresponding to each target oil and gas well location, determine the oil and gas reservoir formation interval based on the minimum and maximum well-reservoir distances, and divide the oil and gas reservoir formation interval into multiple distance intervals according to a preset distance interval.

[0035] The calculation module is used to calculate the oil and gas well production performance value corresponding to each distance interval, and take the oil reservoir formation probability of the distance interval corresponding to the largest production performance value as the benchmark oil reservoir formation probability.

[0036] The construction module is used to calculate the accumulation probability corresponding to each distance interval based on the baseline accumulation probability and the oil and gas production performance value corresponding to each distance interval, and to construct an accumulation prediction model based on each distance interval and the accumulation probability corresponding to each distance interval. The accumulation prediction model is used to predict the accumulation probability distribution characteristics of the target area.

[0037] A computer device includes a memory and a processor, the memory storing a computer program, characterized in that the processor executes the computer program to implement the steps of the method for constructing a fracture-controlled hydrocarbon accumulation prediction model as described in any of the above embodiments.

[0038] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method for constructing a fracture-controlled hydrocarbon accumulation prediction model as described in any of the above embodiments.

[0039] The above-mentioned method and apparatus for constructing the fracture-controlled hydrocarbon accumulation prediction model digitizes key parameters (i.e., the hydrocarbon accumulation probability corresponding to the distance between the hydrocarbon accumulation control fracture location and the hydrocarbon accumulation well location) based on fracture distance and related information of oil and gas wells, and then establishes a hydrocarbon accumulation prediction model between the hydrocarbon accumulation probability and fracture distance, thereby quantitatively characterizing the hydrocarbon accumulation control effect of fractures. Attached Figure Description

[0040] Figure 1 This is a flowchart illustrating the construction method of a fracture-controlled hydrocarbon accumulation prediction model in one embodiment.

[0041] Figure 2 This is a flowchart illustrating the construction method of a fracture-controlled hydrocarbon accumulation prediction model in one embodiment;

[0042] Figure 3 This is a structural block diagram of a device for constructing a fracture-controlled hydrocarbon accumulation prediction model in one embodiment.

[0043] Figure 4 This is an internal structural diagram of a computer device in one embodiment;

[0044] Figure 5This is a histogram showing the number of oil and gas wells in the target layer and their distance from fractures in one embodiment.

[0045] Figure 6 This is a fitting relationship for the probability of fracture-controlled mineralization in the target region in one embodiment;

[0046] Figure 7 This is a probability distribution map of fracture-controlled reservoirs in the target stratigraphic region of one embodiment. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0048] Example 1

[0049] In this embodiment, as Figure 1 As shown, a method for constructing a fracture-controlled hydrocarbon accumulation prediction model is provided, which includes:

[0050] Step 110: Obtain the location of each target oil and gas well in the target area and the location of the reservoir-controlling fracture corresponding to each target oil and gas well location.

[0051] In this embodiment, basic data for the target area is determined, including seismic data, drilling data, and well logging data. Well logging data is extracted from the basic data and analyzed to obtain the location information of oil and gas wells, including well numbers and well coordinates, thus determining the location of the target oil and gas wells. Seismic interpretation techniques are used to identify the spatial distribution characteristics of faults and determine the location of reservoir-controlling faults. Once the location of the target oil and gas wells is determined, the correspondence between the wells and the reservoir-controlling faults is established by combining the well location information with the location of the reservoir-controlling faults. Then, based on this correspondence and the location of the target oil and gas wells, the location of the reservoir-controlling faults corresponding to the target wells is determined. In this embodiment, multiple target oil and gas well locations may exist. For example, the target oil and gas well location may be determined as A. i A i The corresponding fault location controlling the reservoir is S. ij A i Let S be the location of the i-th target oil and gas well. ij Let j be the location of the reservoir-controlling fault corresponding to the location of the i-th oil and gas well, where 1 <i,1<j。

[0052] In one embodiment, the location of the target oil and gas well and the location of the reservoir-controlling fracture corresponding to the location of the target oil and gas well can also be obtained through an input device.

[0053] In one embodiment, the location of the target oil and gas well and the location of the reservoir-controlling fracture corresponding to the target oil and gas well location can also be obtained from the storage medium.

[0054] Step 120: Calculate the well-reservoir distance between the location of each target oil and gas well and the location of the reservoir-controlling fault corresponding to each target oil and gas well location; determine the oil and gas reservoir formation interval based on the minimum and maximum well-reservoir distances; and divide the oil and gas reservoir formation interval into multiple distance intervals according to a preset distance interval.

[0055] Once the locations of the target oil and gas wells and the corresponding reservoir-controlling fractures are determined, the distances between each target oil and gas well location and its corresponding reservoir-controlling fracture location are calculated, resulting in a distance set. Specifically: the target oil and gas well location is identified as A1; the reservoir-controlling fracture location corresponding to A1 is identified as S... 1j ; Calculate each S 1j The distances between each point and A1 are used to obtain the well distance set.

[0056] In this embodiment, the oil and gas reservoir region is determined based on the minimum and maximum well-reservoir distances. This region is then divided into multiple distance intervals according to a preset distance interval. Specifically, the minimum and maximum well-reservoir distances are selected from the set of well-reservoir distances. Next, the oil and gas reservoir region is determined based on these two distances, with the minimum distance used as the first endpoint and the maximum distance used as the second endpoint. Finally, the oil and gas reservoir region is further divided into multiple distance intervals according to the preset distance interval.

[0057] In one embodiment, the hydrocarbon accumulation zone can be divided into 6 distance intervals, or into 10 distance intervals, or into any specific number of distance intervals from 6 to 10; no specific limitation is made here.

[0058] In this embodiment, it is detected whether the minimum well-dwell distance selected from the well-dwell distance set is an integer. If the minimum well-dwell distance is not an integer, it is rounded down to obtain a first rounded value, which is used as an end value of the oil and gas accumulation interval. It is also detected whether the maximum well-dwell distance selected from the well-dwell distance set is an integer. If the maximum well-dwell distance is not an integer, it is rounded up to obtain a second rounded value, which is used as an end value of the oil and gas accumulation interval.

[0059] Step 130: Calculate the oil and gas well production performance value corresponding to each distance interval, and take the oil reservoir formation probability of the distance interval corresponding to the largest production performance value as the benchmark oil reservoir formation probability.

[0060] In this embodiment, the production performance value of oil and gas wells can be the number of oil and gas wells or the cumulative daily production capacity of oil and gas wells; no specific limitation is made here.

[0061] Specifically, after determining the distance intervals, the oil and gas production performance value corresponding to each distance interval is further calculated to obtain the first, second, and third oil and gas production performance values ​​for the first distance interval. The largest production performance value among these three values ​​is then identified, and the hydrocarbon accumulation probability of the distance interval corresponding to the largest production performance value is taken as the baseline hydrocarbon accumulation probability. For example, when the first oil and gas production performance value is the largest, the hydrocarbon accumulation probability of the first distance interval is determined as the baseline hydrocarbon accumulation probability; when the second oil and gas production performance value is the largest, the hydrocarbon accumulation probability of the second distance interval is determined as the baseline hydrocarbon accumulation probability; and when the third oil and gas production performance value is the largest, the hydrocarbon accumulation probability of the third distance interval is determined as the baseline hydrocarbon accumulation probability.

[0062] In one embodiment, the baseline accumulation probability is set to 100%.

[0063] Step 140: Calculate the reservoir formation probability corresponding to each distance interval based on the baseline reservoir formation probability and the oil and gas production performance value corresponding to each distance interval, and construct a reservoir formation prediction model based on each distance interval and the reservoir formation probability corresponding to each distance interval. The reservoir formation prediction model is used to predict the reservoir formation probability distribution characteristics of the target area.

[0064] Once the baseline hydrocarbon accumulation probability is determined, the hydrocarbon accumulation probability corresponding to each distance interval is calculated. Specifically, the hydrocarbon production performance value corresponding to each distance interval is calculated, and then the hydrocarbon accumulation probability corresponding to each distance interval is further calculated based on the baseline hydrocarbon accumulation probability and the hydrocarbon production performance value corresponding to each distance interval. For example, if the baseline hydrocarbon accumulation probability is f, the maximum hydrocarbon production performance value is P, and the hydrocarbon generation performance value corresponding to each distance interval is P0. i P i Let be the oil and gas production performance value of the i-th distance interval, then the probability of reservoir formation corresponding to the distance interval is:

[0065]

[0066] Among them, fi i P represents the probability of accumulation corresponding to the distance interval. i Let be the oil and gas production performance value of the i-th distance interval, P be the oil and gas production performance value of the distance interval corresponding to the baseline accumulation probability, and f be the baseline accumulation probability, which is the accumulation probability of the distance interval with the maximum oil and gas production performance value.

[0067] In this embodiment, after calculating the hydrocarbon accumulation probability of the distance interval, the relationship between the hydrocarbon accumulation probability and the distance interval is determined. Specifically, when the distance interval includes a first distance interval, a second distance interval, and a third distance interval, and the hydrocarbon accumulation probability corresponding to the first distance interval is f1, the hydrocarbon accumulation probability corresponding to the second distance interval is f2, and the hydrocarbon accumulation probability corresponding to the third distance interval is 3, the relationship between the hydrocarbon accumulation probability and the distance interval is:

[0068] (First distance interval → 1, second distance interval → 2, third distance interval → 3)

[0069] Furthermore, an oil and gas accumulation prediction model is constructed based on the relationship between the probability of oil and gas accumulation and the distance interval. The specific process is as follows:

[0070] (1) Construct an initial hydrocarbon accumulation prediction model. Train the initial hydrocarbon accumulation prediction model using the first distance interval →f1 and adjust the parameters of the initial hydrocarbon accumulation probability model. Then, use the second distance interval →f2 to adjust the parameters in the hydrocarbon accumulation probability model. Finally, continue to adjust the parameters in the hydrocarbon accumulation probability model according to the third distance interval →f3. This ensures that the final hydrocarbon accumulation probability model satisfies the following conditions: the difference between the first prediction result obtained from the first distance interval and f1 is within a preset difference range; the difference between the second prediction result obtained from the second distance interval and f2 is within a preset difference range; and the difference between the third prediction result obtained from the third distance interval and f3 is within a preset difference range.

[0071] The expression for the hydrocarbon accumulation prediction model is:

[0072] P f =We Rl

[0073] Among them, P f Let P be the probability of hydrocarbon accumulation, 0 ≤ P f ≤1; l is the coefficient related to the two endpoints of the distance interval containing the well-reservoir distance; e is a constant coefficient, R is a constant, and W is the coefficient relating the reservoir formation probability to the distance interval. In this embodiment, the coefficient related to the two endpoints of the distance interval containing the well-reservoir distance is represented by the average value of the distance interval. For example, if the distance interval is [1, 2], then it is (1+1)÷2.

[0074] In this embodiment, based on the fracture distance and oil and gas well related information, key parameters (i.e., the probability of hydrocarbon accumulation corresponding to the distance between the location of the controlling fracture and the location of the oil and gas well) are digitized, and then a hydrocarbon accumulation prediction model between the probability of hydrocarbon accumulation and the fracture distance is established, thereby quantitatively characterizing the role of fracture in controlling oil and gas.

[0075] In one embodiment, establishing a reservoir formation probability and reservoir formation prediction model for each interval can also be as follows: Establish a model fitting the relationship between reservoir formation probability and fault distance, where the coefficient related to the two endpoints of the distance interval containing the well-reservoir distance is the average of the two endpoints of the interval. For example, when the reservoir formation probability is A, and the interval corresponding to the reservoir formation probability is [S1, S2], then the coefficient related to the two endpoints of the distance interval containing the well-reservoir distance is extracted as (S1+S2)÷2, that is, the reservoir formation probability corresponding to the fault distance (S1+S2)÷2 is A. The reservoir formation prediction model constructed at this time is a model that predicts the reservoir formation probability of oil and gas wells based on fault distance. The expression of the stable reservoir formation prediction model formed at this time is:

[0076] P f =1.476e -0.0006l

[0077] Among them, P f Let P be the probability of hydrocarbon accumulation, 0 ≤ P f ≤1; l is the average of the two endpoints of the distance interval between the well and the reservoir; e is a constant coefficient.

[0078] It should be understood that, although Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0079] In one embodiment, calculating the accumulation probability corresponding to each distance interval based on the baseline accumulation probability and the corresponding oil and gas production performance values ​​of each distance interval includes:

[0080] 1-1) Using the maximum production performance value as the benchmark production performance value, obtain the production performance value corresponding to each distance interval.

[0081] In this embodiment, the probability of hydrocarbon accumulation for each distance interval is calculated based on the baseline accumulation probability and the corresponding hydrocarbon production performance values. This requires first calculating the production performance value for each distance interval. Specifically, the maximum production performance value is first determined as the baseline production performance value, and then the production performance value for each distance interval is calculated.

[0082] In this embodiment, there is a one-to-one correspondence between the benchmark production performance value and the benchmark hydrocarbon accumulation probability.

[0083] In one embodiment, when the production performance value is the number of oil and gas wells, the maximum number of oil and gas wells existing in the distance interval is determined as the benchmark production performance value; and the number of oil and gas wells corresponding to each distance interval is calculated.

[0084] In one embodiment, when the production performance value is the cumulative daily production capacity value of oil and gas, the maximum cumulative daily production capacity value existing in the distance interval is determined as the benchmark production performance value, and the cumulative daily production capacity value corresponding to each distance interval is calculated.

[0085] 1-2) For each distance interval, calculate the ratio of the production performance value corresponding to the distance interval to the benchmark production performance value, and calculate the oil and gas accumulation probability corresponding to the distance interval based on the ratio and the benchmark oil and gas accumulation probability.

[0086] After calculating the production performance value corresponding to each distance interval, the probability of reservoir formation corresponding to each distance interval is further calculated. Specifically, the ratio between the production performance value corresponding to each distance interval and the benchmark production performance value is calculated, and the product of this ratio and the benchmark probability of reservoir formation is calculated. This product is the probability of reservoir formation corresponding to each distance interval.

[0087] In one embodiment, obtaining the locations of each target oil and gas well in the target area and the locations of the reservoir-controlling fractures corresponding to each target oil and gas well location includes:

[0088] 2-1) Determine the oil and gas well data of each oil and gas well in the target area and the reservoir-controlling fracture data corresponding to the oil and gas well data. The oil and gas well data includes the location and production of the oil and gas wells, and the reservoir-controlling fracture data includes the degree and location of the fractures.

[0089] Specifically, the oil and gas well is located at A. i The oil and gas well production rate corresponding to the location of the oil and gas well is h. i A i h represents the location of the i-th oil and gas well. ij Let T be the oil and gas production rate corresponding to the i-th oil and gas well location. The location of the reservoir-controlling fault corresponding to the oil and gas well location is T. ij The degree of fracture corresponding to the location of the fault controlling the reservoir is k. ii T ij Let k be the location of the j-th reservoir-controlling fault corresponding to the location of the i-th oil and gas well. ii The degree of fracture corresponding to the j-th reservoir-controlling fracture location at the i-th oil and gas well location.

[0090] 2-2) Detect whether the production of each oil and gas well has reached the preset production. When the production of the oil and gas well reaches the preset production, the location of the oil and gas well corresponding to the production of the oil and gas well is determined as the target oil and gas well location.

[0091] In this embodiment, the process of determining the location of the target oil and gas well specifically involves: detecting whether the production rate of each oil and gas well has reached a preset production rate; when the production rate reaches the preset production rate, the location of the oil and gas well corresponding to that production rate is determined as the target oil and gas well location. For example, detecting the production rate h of the oil and gas well corresponding to the location of each i-th oil and gas well. ij Is it less than the preset output, when h ij If the production rate is less than the preset target, it indicates that the research value of the i-th oil and gas well is low. Therefore, the well at location A will not be selected. i If the location is determined as the target oil and gas well location, then the i-th oil and gas well has higher research value. Conversely, if the location is not specified, then the i-th oil and gas well location is considered the target location. i The location of the target oil and gas well has been identified.

[0092] In this embodiment, the target oil and gas well location may include multiple locations or only one location; no specific limitation is made here.

[0093] 2-3) Detect whether the degree of fracture of each controlled reservoir fracture reaches the preset degree of fracture. When the degree of fracture reaches the preset degree of fracture, the fracture position corresponding to the degree of fracture is determined as the target controlled reservoir fracture position.

[0094] Once the location of the target oil and gas well is determined, the data of each reservoir-controlling fracture corresponding to the target oil and gas well location are determined, and then the location of the target reservoir-controlling fracture is determined. Specifically, the location of each reservoir-controlling fracture corresponding to the target oil and gas well location is detected, and the degree of fracture of each reservoir-controlling fracture location is further detected to see if it reaches the preset degree of fracture. When the degree of fracture reaches the preset degree of fracture, it indicates that the reservoir-controlling fracture location has high research value, and then each reservoir-controlling fracture location that reaches the preset degree of fracture is determined as the target reservoir-controlling fracture location.

[0095] In one embodiment, determining each reservoir-controlling fracture location that has reached a preset fracture level as the target reservoir-controlling fracture location can be achieved by: determining each reservoir-controlling fracture location that has reached a preset fracture level, detecting the distance between each reservoir-controlling fracture location and the target oil and gas well location, and determining the reservoir-controlling fracture location corresponding to the shortest distance between the location and the target oil and gas well location as the target reservoir-controlling fracture location.

[0096] In this embodiment, limiting the production rate of the target oil and gas well to a certain level when determining its location is to ensure the relevance and effectiveness of the research. High-yield oil and gas wells often indicate abundant oil and gas resources and favorable reservoir conditions in their respective areas, making them more likely to be significantly affected by reservoir-controlling fractures. By studying these high-yield oil and gas wells and their corresponding reservoir-controlling fractures, a deeper understanding of the controlling role of fractures in oil and gas reservoirs can be gained. Secondly, limiting the location of reservoir-controlling fractures to a certain level when determining the location of the target oil and gas well is also based on the important role of fractures in the formation and distribution of oil and gas reservoirs. As fractures that control oil and gas reservoirs, the scale and properties of reservoir-controlling fractures directly affect the generation, migration, accumulation, and dissipation of oil and gas. Therefore, studying reservoir-controlling fractures to a certain level can better reveal the intrinsic relationship between fractures and oil and gas reservoirs, providing a clearer direction for oil and gas exploration.

[0097] In one embodiment, after constructing an oil and gas accumulation prediction model based on the distance interval and the corresponding probability of oil and gas accumulation, the method further includes:

[0098] 3-1) Obtain the verification locations of oil and gas wells in the target area, and the verification locations of reservoir-controlling fractures corresponding to the verification locations of the oil and gas wells.

[0099] In this embodiment, to verify the accuracy of the hydrocarbon accumulation prediction model and improve its generalization ability, it is necessary to validate the model. Specifically, the locations of oil and gas wells and the corresponding reservoir-controlling faults in the target area are now determined.

[0100] In this embodiment, the verification location of the oil and gas well may be the same as the location of the target oil and gas well; it may not be a location within the target oil and gas well location; it may also be partially the same as the location of the target oil and gas well location and partially different from the location of the target oil and gas well location; no specific limitation is made here.

[0101] In one embodiment, the reservoir-controlling fracture verification location corresponding to the oil and gas well verification location is: the location of the reservoir-controlling fracture closest to the oil and gas well verification location.

[0102] In one embodiment, the reservoir-controlling fracture verification location corresponding to the oil and gas well verification location is: the location of the reservoir-controlling fracture closest to the oil and gas well verification location and whose fracture degree reaches a preset fracture degree.

[0103] 3-2) Determine the distance difference between the verification location of the oil and gas well and the verification location of the reservoir-controlling fracture, the verification value of the oil and gas well production performance corresponding to the distance difference, and the total production performance value of the oil and gas well in the target area.

[0104] 3-3) Input the distance difference into the hydrocarbon accumulation prediction model, and use the hydrocarbon accumulation prediction model to process the distance difference to obtain the predicted distance interval corresponding to the distance difference and the hydrocarbon accumulation probability in the predicted distance interval.

[0105] 3-4) Based on the hydrocarbon accumulation verification probability and the total production performance value, calculate the predicted production performance value corresponding to the predicted distance interval.

[0106] After obtaining the hydrocarbon accumulation verification probability and the total production performance of oil and gas wells in the target area, the predicted production performance value corresponding to the predicted distance interval is calculated. Specifically, the product between the total production performance value and the hydrocarbon accumulation verification probability is calculated to obtain the predicted production performance value corresponding to the predicted distance interval.

[0107] 3-5) Check whether the difference between the predicted production performance value and the verified production performance value of the oil and gas well is within the preset difference range.

[0108] Specifically, a preset difference range is set, and then the difference between the predicted production performance value and the verified production performance value of the oil and gas well is checked to see if it is within the preset difference range. When the difference between the predicted production performance value and the verified production performance value of the oil and gas well is within the preset difference range, it means that the prediction result of the reservoir formation prediction model has reached the preset accuracy; otherwise, it means that the accuracy of the prediction result of the reservoir formation prediction model is low.

[0109] In one embodiment, the preset difference range is greater than 85%.

[0110] 3-6) When the difference between the predicted production performance value and the verified production performance value of the oil and gas well is within the preset difference range, the reservoir formation prediction model is determined.

[0111] In this implementation, when the difference between the predicted production performance value and the verified production performance value of the oil and gas well is within a preset difference range, it indicates that the generalization ability and accuracy of the hydrocarbon accumulation prediction model are both high, and the hydrocarbon accumulation prediction model is thus determined. When the difference between the predicted production performance value and the verified production performance value of the oil and gas well is not within the preset difference range, it indicates that the generalization ability of the hydrocarbon accumulation prediction model is weak and the accuracy is low, and further adjustments to the parameters in the hydrocarbon accumulation prediction model are needed until the generalization ability of the hydrocarbon accumulation prediction model is strong and the accuracy is high.

[0112] In this embodiment, further validation of the hydrocarbon accumulation prediction model after its construction ensures its reliability in practical applications. A good model performance on the validation set makes its application in actual oil and gas exploration and development more practical and accurate. Furthermore, analyzing the model's validation performance reveals potential problems and shortcomings, such as overfitting or underfitting. Based on this information, the model can be further adjusted and optimized to improve its predictive performance, thereby determining its accuracy, stability, and generalization ability, demonstrating its reliable predictive capability.

[0113] In one embodiment, after constructing an oil and gas accumulation prediction model based on each distance interval and the corresponding probability of oil and gas accumulation for each distance interval, the method further includes:

[0114] 4-1) Obtain the distance of the reservoir-controlling fault in the target area, input the distance of the reservoir-controlling fault into the reservoir formation prediction model, and use the reservoir formation prediction model to calculate the distance of the reservoir-controlling fault to obtain the reservoir formation probability in the distance interval corresponding to the distance of the reservoir-controlling fault.

[0115] Before predicting the hydrocarbon accumulation probability of the oil and gas wells within the target range, it is necessary to first determine the location of each well and the corresponding hydrocarbon accumulation-controlling fault location. This involves determining the location of each well and its corresponding hydrocarbon accumulation-controlling fault location, calculating the distance between each well location and its corresponding fault location, and obtaining the distance for each hydrocarbon accumulation-controlling fault. Then, this distance is input into the hydrocarbon accumulation probability model, and the model is used to calculate the hydrocarbon accumulation probability for each distance within its corresponding range.

[0116] 4-2) Determine the basic contour image of the target area, and combine the basic contour image with the hydrocarbon accumulation probability to generate a fault-controlled hydrocarbon accumulation probability distribution image.

[0117] Specifically, a basic contour map is determined, and the hydrocarbon accumulation probability of each distance interval corresponding to the controlled hydrocarbon accumulation fault distance is fused and superimposed onto the basic contour map. For example, the hydrocarbon accumulation probability can be superimposed onto the basic contour map in the form of color or grayscale values, so that areas with different hydrocarbon accumulation probabilities can be clearly distinguished on the image. In this embodiment, the fault system information of the target area can be combined to mark the faults on the basic contour map. Based on the controlling effect of the faults on hydrocarbon accumulation, the distribution of hydrocarbon accumulation probability near the faults is adjusted. For example, a fault may be a channel or barrier for hydrocarbon migration, which will affect the specific distribution of hydrocarbon accumulation probability.

[0118] In this embodiment, by generating a fault-controlled hydrocarbon accumulation probability distribution image, the geological characteristics of the target area, such as stratigraphic thickness, lithology, and structure, can be intuitively displayed. Combined with the accumulation probability, the potential distribution of underground oil and gas reservoirs is further presented in image form, simplifying and visualizing complex geological information. Furthermore, by overlaying fault information onto contour images and combining it with the accumulation probability, the specific impact of faults on hydrocarbon accumulation can be analyzed, such as whether faults act as channels for hydrocarbon migration or as barriers to hydrocarbon accumulation. The generated fault-controlled hydrocarbon accumulation probability distribution image can provide scientific decision support for oil and gas exploration and development. Whether it's selecting exploration targets, formulating exploration plans, or optimizing development plans, more rational and accurate decisions can be made based on these images.

[0119] Example 2

[0120] In this embodiment, as Figure 2 As shown, a method for constructing a fracture-controlled hydrocarbon accumulation prediction model is provided, which includes:

[0121] Step 210: Select the location of oil and gas wells and reservoir-controlling faults in the target area.

[0122] In this embodiment, oil and gas wells and reservoir-controlling fractures that have been discovered in the target area are selected. The discovered oil and gas wells in the target area are those that have encountered oil and gas and have a certain production rate, with a daily production exceeding a certain level. Reservoir-controlling fractures are fractures of a certain scale within the study area that are closely related to oil and gas, typically oil (gas) source fractures or important oil and gas migration channels. Furthermore, the locations of the oil and gas wells and reservoir-controlling fractures are determined, i.e., the locations of the oil and gas wells and the reservoir-controlling fractures.

[0123] In one embodiment, the location of oil and gas wells and the location of reservoir-controlling fractures can be determined by image analysis. Specifically, images of the oil and gas wells and reservoir-controlling fractures that have been discovered in the target area are acquired, the images are analyzed, the locations of oil and gas wells and reservoir-controlling fractures are determined in the images, and the actual locations of oil and gas wells and reservoir-controlling fractures are calculated according to the size of the image and the actual scale.

[0124] Step 220: Randomly select oil and gas well locations and divide them into a standard set and a validation set.

[0125] After obtaining the locations of oil and gas wells, these locations are divided into a standard set and a validation set. The standard set serves as the foundational data for constructing a fracture-controlled hydrocarbon accumulation prediction model; the validation set contains the validation data used to verify this model. Specifically, the oil and gas wells are randomly divided into two equal groups: Group 1 and Group 2. The locations of the oil and gas wells in Group 1 are defined as the standard set, and the locations of the oil and gas wells in Group 2 are defined as the validation set.

[0126] In one embodiment, the oil and gas wells can be randomly divided into two groups of unequal size, with the group with the larger data volume designated as the first group and the group with the smaller data volume designated as the second group; wherein, the oil and gas well locations corresponding to the oil and gas wells in the first group are determined as the standard set, and the oil and gas well locations corresponding to the oil and gas wells in the second group are determined as the verification set.

[0127] In one embodiment, the oil and gas wells can be randomly divided into two groups of unequal size, with the group with the larger data volume designated as the first group and the group with the smaller data volume designated as the second group; wherein, the locations of the oil and gas wells corresponding to the oil and gas wells in the first group are determined as the validation set, and the locations of the oil and gas wells corresponding to the oil and gas wells in the second group are determined as the standard set.

[0128] In this embodiment, oil and gas well locations are divided into a standard set and a validation set. The standard set is used to train and learn the fracture-controlled hydrocarbon accumulation prediction model. By analyzing and processing the oil and gas well locations in the standard set and their corresponding reservoir-controlling fracture data, the fracture-controlled hydrocarbon accumulation prediction model can establish an accurate understanding of the hydrocarbon accumulation environment. The validation set data is used to test the fracture-controlled hydrocarbon accumulation prediction model. If the model performs well on the validation data, it can achieve good prediction results in practical applications. Furthermore, the validation set data can also identify and correct overfitting problems that may exist during the training process of the fracture-controlled hydrocarbon accumulation prediction model.

[0129] Step 230: Obtain the distance information between the oil and gas well locations and reservoir-controlling fault locations in the standard set.

[0130] Once the standard set and validation set of oil and gas wells are determined, the locations of all oil and gas wells in the standard set are obtained, along with the locations of reservoir-controlling fractures corresponding to those well locations. The distance information between the oil and gas well locations and the reservoir-controlling fracture locations is calculated; specifically, the distance between each oil and gas well and its nearest adjacent fracture is measured. In other words, the oil and gas well locations must first be determined, and the distances between these locations and each reservoir-controlling fracture location must be calculated to obtain a set of distances between the oil and gas well locations and each reservoir-controlling fracture location. The shortest distance in this set is then determined as the distance information between the oil and gas well location and the reservoir-controlling fracture location.

[0131] In one embodiment, the distance information between the location of the oil and gas well and the location of the reservoir-controlling fracture can also be determined by the user through electronic measurement of the image, and then the location of the oil and gas well and the location of the reservoir-controlling fracture can be input into the terminal through an input device, so that the terminal can obtain the location of the oil and gas well and the location of the reservoir-controlling fracture. In this embodiment, the image is the image corresponding to the oil and gas well and the reservoir-controlling fracture that have been discovered in the target area.

[0132] In this embodiment, as shown in Table 1 below, the well name in Table 1 is the location of the oil and gas well, and the distance from the fracture is the distance information between the location of the oil and gas well and the location of the reservoir-controlling fracture.

[0133] Table 1

[0134]

[0135]

[0136] Referring to Table 1 above, the distribution relationship between the number of oil and gas wells and the location of reservoir-controlling faults can be obtained, such as... Figure 5 As shown, the histogram of the number of oil and gas wells in the target area and their distance from the fracture distribution can be seen.

[0137] In one embodiment, the distance information between the location of the oil and gas well and the location of the reservoir-controlling fracture is N data points, where N is a positive integer; in this embodiment, N equals 280.

[0138] Step 240: Divide the distance information between the location of the oil and gas well and the location of the reservoir-controlling fault into several intervals.

[0139] Once the locations of the target oil and gas wells and the corresponding reservoir-controlling fractures are determined, the distances between each target oil and gas well location and its corresponding reservoir-controlling fracture location are calculated, resulting in a distance set. Specifically: the target oil and gas well location is identified as A1; the reservoir-controlling fracture location corresponding to A1 is identified as S... 1j ; Calculate each S 1j The distances between each point and A1 are used to obtain the well distance set.

[0140] In this embodiment, the oil and gas reservoir region is determined based on the minimum and maximum well-reservoir distances. This region is then divided into multiple distance intervals according to a preset distance interval. Specifically, the minimum and maximum well-reservoir distances are selected from the set of well-reservoir distances. Next, the oil and gas reservoir region is determined based on these two distances, with the minimum distance used as the first endpoint and the maximum distance used as the second endpoint. Finally, the oil and gas reservoir region is further divided into multiple distance intervals according to the preset distance interval.

[0141] In one embodiment, the hydrocarbon accumulation zone can be divided into 6 distance intervals, or into 10 distance intervals, or into any specific number of distance intervals from 6 to 10; no specific limitation is made here.

[0142] In this embodiment, it is detected whether the minimum well-dwell distance selected from the well-dwell distance set is an integer. If the minimum well-dwell distance is not an integer, it is rounded down to obtain a first rounded value, which is used as an end value of the oil and gas accumulation interval. It is also detected whether the maximum well-dwell distance selected from the well-dwell distance set is an integer. If the maximum well-dwell distance is not an integer, it is rounded up to obtain a second rounded value, which is used as an end value of the oil and gas accumulation interval.

[0143] In this embodiment, after calculating the distance information between each oil and gas well location and the reservoir-controlling fracture location, several intervals are formed according to the preset division distance and the distance information between each oil and gas well location and the reservoir-controlling fracture location. For example, the first distance between the first well and the nearest adjacent fracture is calculated, the second distance between the second well and the nearest adjacent fracture is calculated, and the third distance between the third well and the nearest adjacent fracture is calculated; several intervals are formed according to the preset division distance, the first distance, the second distance, and the third distance. Specifically: the minimum value among each distance is determined, the sum of the minimum value and the preset division distance is calculated, the minimum value is used as one endpoint of the first interval, and the sum of the minimum value and the preset division distance is used as the other endpoint of the first interval, thus forming the first interval. It is checked whether each distance is within the first interval. When it is within the first interval, the distance interval corresponding to that distance is the first interval. When the distance is not within the first interval, the minimum distance value not within the first interval is used as one endpoint of the second interval, the sum of the minimum distance value and the preset division distance is calculated, and the sum of the minimum distance value and the preset division distance is used as the other endpoint of the second interval, thus forming the second interval. Similarly, the third, fourth, and fifth intervals can be generated based on various distances and preset division distances.

[0144] Step 250: Determine the hydrocarbon accumulation probability corresponding to the distance information between the oil and gas well location and the location of the hydrocarbon accumulation-controlling fault.

[0145] In this embodiment, the probability of hydrocarbon accumulation corresponding to the distance information between the oil and gas well location and the location of the reservoir-controlling fault is the probability of hydrocarbon accumulation corresponding to the interval in which the distance information between the oil and gas well location and the reservoir-controlling fault location is located. After calculating the interval in which the distance information between the oil and gas well location and the reservoir-controlling fault location is located, the probability of hydrocarbon accumulation corresponding to each interval is calculated.

[0146] Specifically, the digital coding standard set relates the fault distance to the probability of hydrocarbon accumulation. For example, the probability of hydrocarbon accumulation corresponding to the interval with the most discovered oil and gas wells or the highest cumulative daily production is assigned a value of 1, and the other intervals are assigned values ​​according to the ratio of the number of discovered oil and gas wells to the number of the most discovered group.

[0147] In one embodiment, the probability of reservoir formation corresponding to the interval with the most oil and gas wells is assigned a value of 1, and the maximum number of oil and gas wells in that interval is obtained. Then, the number of oil and gas wells in each interval is obtained. The ratio between the number of oil and gas wells in each interval and the maximum number is calculated. Using this ratio and the probability of reservoir formation 1, the probability of reservoir formation corresponding to each interval is calculated.

[0148] Step 260: Establish the hydrocarbon accumulation probability and hydrocarbon accumulation prediction model for each interval.

[0149] In this embodiment, after obtaining the hydrocarbon accumulation probability of each interval, a hydrocarbon accumulation prediction model is established using each interval and its corresponding probability. Specifically, a hydrocarbon accumulation prediction model based on the hydrocarbon accumulation probability of each interval is determined through statistical analysis. After the hydrocarbon accumulation prediction model is built, it is cross-validated using a validation set and the locations of the hydrocarbon accumulation-controlling faults corresponding to the validation set. Specifically, the number of oil and gas wells in the validation set and the locations of the hydrocarbon accumulation-controlling faults are used for prediction and verification. If the prediction results of the validation set match the actual results by more than 85%, the next step is performed; otherwise, the corresponding hydrocarbon accumulation prediction model is adjusted and optimized, and the verification is repeated until the match rate reaches or exceeds 85%.

[0150] In one embodiment, establishing a hydrocarbon accumulation probability and hydrocarbon accumulation prediction model for each interval can also be achieved by establishing a model that fits the hydrocarbon accumulation probability with the fault distance, where the fault distance is the average of the two endpoints of the interval. For example, when the hydrocarbon accumulation probability is A, and the interval corresponding to the hydrocarbon accumulation probability is [S1, S2], then the coefficient related to the two endpoints of the distance interval where the well-gas well is located is extracted as (S1+S2)÷2, that is, the hydrocarbon accumulation probability corresponding to the fault distance (S1+S2)÷2 is A. The constructed hydrocarbon accumulation prediction model is then a model that predicts the hydrocarbon accumulation probability of oil and gas wells based on the fault distance, where the fitting relationship in the hydrocarbon accumulation probability model is as follows: Figure 6 As shown. In this embodiment, the expression of the fitted hydrocarbon accumulation prediction model is:

[0151] P f =We Rl

[0152] Among them, P f Let P be the probability of hydrocarbon accumulation, 0 ≤ P f≤1; l is the coefficient related to the two endpoints of the distance interval containing the well-reservoir distance; e is a constant coefficient, R is a constant, and W is the coefficient relating the reservoir formation probability to the distance interval. In this embodiment, the coefficient related to the two endpoints of the distance interval containing the well-reservoir distance is represented by the average value of the distance interval. For example, if the distance interval is [l1, l2], then l is (l1+l1)÷2.

[0153] In one embodiment, the probability distribution characteristics of hydrocarbon accumulation under fault control in the study area are quantitatively characterized. The finalized hydrocarbon accumulation prediction model is applied to the entire study area, and the probability distribution characteristics of hydrocarbon accumulation under fault control are quantitatively characterized. In this embodiment, the hydrocarbon accumulation probability distribution map of the target area is as follows: Figure 7 As shown.

[0154] In this embodiment, based on fracture distance and oil and gas well related information, key parameters are digitized, and a digital model between the probability of hydrocarbon accumulation and fracture distance is established using geostatistical methods, thereby quantitatively characterizing the role of fractures in controlling hydrocarbon accumulation. This method is applicable to areas with some oil and gas discoveries and production capacity, but where the role of fractures in controlling hydrocarbon accumulation is unclear. It can provide effective guidance for subsequent evaluation of fracture effects and identification of favorable exploration areas, enhancing geological understanding and thus gaining widespread application.

[0155] In one embodiment, the expression for a stable hydrocarbon accumulation prediction model is:

[0156] P f =1.476e -0.0006l

[0157] Among them, P f Let P be the probability of hydrocarbon accumulation, 0 ≤ P f ≤1; l is the average of the two endpoints of the distance interval between the well and the reservoir; e is a constant coefficient.

[0158] It should be understood that, although Figure 2 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 2 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0159] Example 3

[0160] In this embodiment, as Figure 3As shown, a device for constructing a fracture-controlled hydrocarbon accumulation prediction model is provided, comprising: an acquisition module 310, a partitioning module 320, a calculation module 330, and a construction module 340.

[0161] The acquisition module 310 is used to acquire the location of each target oil and gas well in the target area and the location of the reservoir-controlling fracture corresponding to each target oil and gas well location.

[0162] The partitioning module 320 is used to calculate the well-reservoir distance between the locations of each target oil and gas well and the locations of the reservoir-controlling faults corresponding to each target oil and gas well location, determine the oil and gas reservoir formation interval based on the minimum and maximum well-reservoir distances, and divide the oil and gas reservoir formation interval into multiple distance intervals according to a preset distance interval.

[0163] The calculation module 330 is used to calculate the oil and gas well production performance value corresponding to each distance interval, and take the oil reservoir formation probability of the distance interval corresponding to the largest production performance value as the benchmark oil reservoir formation probability.

[0164] The construction module 340 is used to calculate the accumulation probability corresponding to each distance interval based on the baseline accumulation probability and the oil and gas production performance value corresponding to each distance interval, and to construct an accumulation prediction model based on each distance interval and the accumulation probability corresponding to each distance interval. The accumulation prediction model is used to predict the accumulation probability distribution characteristics of the target area.

[0165] In this embodiment, the acquisition module 310 acquires the locations of each target oil and gas well in the target area and the corresponding reservoir-controlling fracture locations, and sends the target oil and gas well locations and their corresponding reservoir-controlling fracture locations to the value division module 320. The division module 320 calculates the well-reservoir distance between each target oil and gas well location and its corresponding reservoir-controlling fracture location, determines the oil and gas reservoir formation interval based on the minimum and maximum well-reservoir distances, divides the oil and gas reservoir formation interval into multiple distance intervals according to a preset distance interval, and then sends each distance interval to the calculation module 330. The calculation module 330 calculates the oil and gas well production performance value corresponding to each distance interval, takes the reservoir formation probability of the distance interval corresponding to the largest production performance value as the baseline reservoir formation probability, and then sends the baseline reservoir formation probability to the construction module 340. The construction module 340 calculates the accumulation probability corresponding to each distance interval based on the baseline accumulation probability and the oil and gas production performance value corresponding to each distance interval, and constructs an accumulation prediction model based on each distance interval and the accumulation probability corresponding to each distance interval. The accumulation prediction model is used to predict the accumulation probability distribution characteristics of the target area.

[0166] In one embodiment, the construction module 340 may include a first determining unit and a calculation unit.

[0167] The first determining unit is used to take the maximum production performance value as the benchmark production performance value and obtain the production performance value corresponding to each distance interval.

[0168] The calculation unit is configured to calculate, for each distance interval, the ratio of the production performance value corresponding to the distance interval to the benchmark production performance value, and calculate the oil and gas accumulation probability corresponding to the distance interval based on the ratio and the benchmark oil and gas accumulation probability.

[0169] In one embodiment, the acquisition module 310 may include: a second determining unit, a first detection unit, and a second detection unit.

[0170] The second determining unit is used to determine the oil and gas well data of each oil and gas well in the target area and the reservoir-controlling fracture data corresponding to the oil and gas well data. The oil and gas well data includes the location and production of the oil and gas wells, and the reservoir-controlling fracture data includes the degree and location of the fractures.

[0171] The first detection unit is used to detect whether the production of each oil and gas well has reached the preset production. When the production of the oil and gas well reaches the preset production, the location of the oil and gas well corresponding to the production is determined as the target oil and gas well location.

[0172] The second detection unit is used to detect whether the degree of fracture of each controlled reservoir fracture reaches the preset degree of fracture. When the degree of fracture reaches the preset degree of fracture, the fracture position corresponding to the degree of fracture is determined as the target controlled reservoir fracture position.

[0173] In one embodiment, the apparatus for constructing a fracture-controlled hydrocarbon accumulation prediction model may further include: a location acquisition module, a first determination module, a verification module, a prediction value calculation module, a detection module, and a second determination module.

[0174] The location acquisition module is used to acquire the verification location of oil and gas wells in the target area, and the verification location of the reservoir-controlling fractures corresponding to the verification locations of the oil and gas wells.

[0175] The first determining module is used to determine the distance difference between the oil and gas well verification location and the reservoir-controlling fracture verification location, the oil and gas well production performance verification value corresponding to the distance difference, and the total production performance value of the oil and gas wells in the target area.

[0176] The verification module is used to input the distance difference into the hydrocarbon accumulation prediction model, process the distance difference using the hydrocarbon accumulation prediction model, and obtain the predicted distance interval corresponding to the distance difference and the hydrocarbon accumulation probability in the predicted distance interval.

[0177] The prediction value calculation module is used to calculate the predicted production performance value corresponding to the prediction distance interval based on the oil and gas accumulation verification probability and the total production performance value.

[0178] The detection module is used to detect whether the difference between the predicted production performance value and the verified production performance value of the oil and gas well is within a preset difference range;

[0179] The second determining module is used to determine the reservoir formation prediction model when the detection module determines that the difference between the predicted production performance value and the verified oil and gas well production performance value is within the preset difference range.

[0180] In one embodiment, the production performance value is the number of oil and gas wells or the daily cumulative production capacity of oil and gas wells.

[0181] In one embodiment, the expression of the hydrocarbon accumulation prediction model is:

[0182] P f =We Rl

[0183] Among them, P f Let P be the probability of hydrocarbon accumulation, 0 ≤ P f ≤1; l is the coefficient related to the two endpoints of the distance interval where the well reservoir is located; e is a constant coefficient, R is a constant, and W is the coefficient relating the reservoir formation probability to the distance interval.

[0184] In one embodiment, the apparatus for constructing a fracture-controlled hydrocarbon accumulation prediction model may further include: a data acquisition module and a data generation module.

[0185] The data acquisition module is used to acquire the distance of the reservoir-controlling fault in the target area, input the distance of the reservoir-controlling fault into the reservoir formation prediction model, and use the reservoir formation prediction model to calculate the reservoir-controlling fault distance to obtain the reservoir formation probability in the distance interval corresponding to the reservoir-controlling fault distance.

[0186] The generation module is used to determine the basic contour image of the target area, and combine the basic contour image with the hydrocarbon accumulation probability to generate a fault-controlled hydrocarbon accumulation probability distribution image.

[0187] Specific limitations regarding the construction apparatus for the fracture-controlled hydrocarbon accumulation prediction model can be found in the above-mentioned limitations on the construction method of the fracture-controlled hydrocarbon accumulation prediction model, and will not be repeated here. Each unit in the aforementioned construction apparatus for the fracture-controlled hydrocarbon accumulation prediction model can be implemented entirely or partially through software, hardware, or a combination thereof. These units can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each unit.

[0188] Example 4

[0189] In this embodiment, a computer device is provided. Its internal structure diagram can be shown as follows: Figure 4 As shown, the computer device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computational and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs, and also contains a database that stores all relevant data involved in and generated by the aforementioned method for constructing a fracture-controlled hydrocarbon accumulation prediction model. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface is used to communicate with other computer devices that have deployed application software. When the processor executes the computer program, it implements a method for constructing a fracture-controlled hydrocarbon accumulation prediction model. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0190] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0191] In one embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of the method for constructing a fracture-controlled hydrocarbon accumulation prediction model as described in any of the above embodiments.

[0192] Example 5

[0193] In this embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of the method for constructing a fracture-controlled hydrocarbon accumulation prediction model as described in any of the above embodiments.

[0194] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0195] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0196] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for constructing a fracture-controlled hydrocarbon accumulation prediction model, characterized in that, include: Obtain the location of each target oil and gas well in the target area and the location of the reservoir-controlling fracture corresponding to each target oil and gas well location; Calculate the well-reservoir distance between the locations of each target oil and gas well and the locations of the reservoir-controlling faults corresponding to each target oil and gas well location, determine the oil and gas reservoir formation interval based on the minimum and maximum well-reservoir distances, and divide the oil and gas reservoir formation interval into multiple distance intervals according to a preset distance interval; Calculate the oil and gas well production performance value corresponding to each distance interval, and take the oil reservoir formation probability of the distance interval corresponding to the largest production performance value as the benchmark oil reservoir formation probability; The probability of hydrocarbon accumulation for each distance interval is calculated based on the baseline hydrocarbon accumulation probability and the oil and gas production performance value corresponding to each distance interval. A hydrocarbon accumulation prediction model is constructed based on each distance interval and the hydrocarbon accumulation probability corresponding to each distance interval. The hydrocarbon accumulation prediction model is used to predict the hydrocarbon accumulation probability distribution characteristics of the target area.

2. The method according to claim 1, characterized in that, The calculation of the accumulation probability for each distance interval based on the baseline accumulation probability and the corresponding oil and gas production performance values ​​for each distance interval includes: Using the maximum production performance value as the benchmark production performance value, obtain the production performance value corresponding to each distance interval; For each distance interval, the ratio of the production performance value corresponding to the distance interval to the benchmark production performance value is calculated. Based on the ratio and the benchmark oil and gas accumulation probability, the oil and gas accumulation probability corresponding to the distance interval is calculated.

3. The method according to claim 1, characterized in that, The acquisition of the locations of each target oil and gas well in the target area and the locations of the reservoir-controlling fractures corresponding to each target oil and gas well location includes: Determine the oil and gas well data and the reservoir-controlling fracture data corresponding to each oil and gas well in the target area. The oil and gas well data includes the location and production of the oil and gas wells, and the reservoir-controlling fracture data includes the degree and location of the fractures. The system detects whether the production of each oil and gas well has reached the preset production rate. When the production of the oil and gas well reaches the preset production rate, the location of the oil and gas well corresponding to the production rate is determined as the target oil and gas well location. The degree of fracture of each controlled reservoir is detected to see if it reaches the preset degree of fracture. When the degree of fracture reaches the preset degree of fracture, the fracture position corresponding to the degree of fracture is determined as the target controlled reservoir fracture position.

4. The method according to claim 1, characterized in that, After constructing the hydrocarbon accumulation prediction model based on the distance interval and the hydrocarbon accumulation probability corresponding to the distance interval, the method further includes: Obtain the verification locations of oil and gas wells in the target area, and the verification locations of reservoir-controlling fractures corresponding to the verification locations of the oil and gas wells; Determine the distance difference between the verification location of the oil and gas well and the verification location of the reservoir-controlling fracture, the verification value of the oil and gas well production performance corresponding to the distance difference, and the total production performance value of the oil and gas wells in the target area; The distance difference is input into the hydrocarbon accumulation prediction model, and the distance difference is processed by the hydrocarbon accumulation prediction model to obtain the predicted distance interval corresponding to the distance difference and the hydrocarbon accumulation probability in the predicted distance interval; Based on the hydrocarbon accumulation verification probability and the total production performance value, the predicted production performance value corresponding to the predicted distance interval is calculated. The difference between the predicted production performance value and the verified production performance value of the oil and gas well is checked to see if it is within a preset difference range. When the difference between the predicted production performance value and the verified production performance value of the oil and gas well is within the preset difference range, the reservoir formation prediction model is determined.

5. The method according to claim 3, characterized in that, The production performance value is the number of oil and gas wells or the daily cumulative production capacity of oil and gas wells.

6. The method according to any one of claims 1-5, characterized in that, The expression for the hydrocarbon accumulation prediction model is: P f =We Rl Among them, P f Let P be the probability of hydrocarbon accumulation, 0 ≤ P f ≤1; l is the coefficient related to the two endpoints of the distance interval where the well reservoir is located; e is a constant coefficient, R is a constant, and W is the coefficient relating the reservoir formation probability to the distance interval.

7. The method according to any one of claims 1-5, characterized in that, After constructing the hydrocarbon accumulation prediction model based on each distance interval and the corresponding hydrocarbon accumulation probability, the method further includes: The distance of the reservoir-controlling fault in the target area is obtained, and the distance of the reservoir-controlling fault is input into the reservoir formation prediction model. The reservoir formation prediction model is used to calculate the distance of the reservoir-controlling fault to obtain the reservoir formation probability in the distance interval corresponding to the distance of the reservoir-controlling fault. Determine the basic contour image of the target area, and combine the basic contour image with the hydrocarbon accumulation probability to generate a fault-controlled hydrocarbon accumulation probability distribution image.

8. A device for constructing a fracture-controlled hydrocarbon accumulation prediction model, characterized in that, include: The acquisition module is used to acquire the location of each target oil and gas well in the target area and the location of the reservoir-controlling fracture corresponding to each target oil and gas well location; The division module is used to calculate the well-reservoir distance between the locations of each target oil and gas well and the locations of the reservoir-controlling faults corresponding to each target oil and gas well location, determine the oil and gas reservoir formation interval based on the minimum and maximum well-reservoir distances, and divide the oil and gas reservoir formation interval into multiple distance intervals according to a preset distance interval. The calculation module is used to calculate the oil and gas well production performance value corresponding to each distance interval, and take the oil reservoir formation probability of the distance interval corresponding to the largest production performance value as the benchmark oil reservoir formation probability. The construction module is used to calculate the accumulation probability corresponding to each distance interval based on the baseline accumulation probability and the oil and gas production performance value corresponding to each distance interval, and to construct an accumulation prediction model based on each distance interval and the accumulation probability corresponding to each distance interval. The accumulation prediction model is used to predict the accumulation probability distribution characteristics of the target area.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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