Recognition method and device of hydrocarbon reservoir, electronic equipment and storage medium

Abstract

The invention provides a hydrocarbon reservoir identification method and device, electronic equipment and a storage medium. The identification method comprises the steps of obtaining a pre-created well logging interpretation intersection chart; according to the data sources corresponding to the horizontal and vertical coordinates in the logging interpretation intersection chart, logging characteristic values are obtained; projecting the logging characteristic value into the logging interpretation intersection chart to obtain a projection position of the logging characteristic value in the logging interpretation intersection chart; and determining a hydrocarbon reservoir identification result of the reservoir represented by the projection position based on the projection position and a pre-created identification rule. By adopting the technical scheme provided by the invention, intelligent batch processing can be carried out without manual layer-by-layer explanation of researchers, and the efficiency of identifying the hydrocarbon reservoir is improved.

Description

Technical Field

[0001] The present application relates to the technical field of geophysical exploration, and in particular, to a method, device, electronic device, and storage medium for identifying oil and gas layers. Background Art

[0002] Oil and gas layer identification is an extremely crucial and important task in log interpretation and evaluation. Using interpretation charts for fluid identification is an important and commonly used technical method. Interpretation charts are graphs used to represent the relationships between formation logging parameters or other parameters. Logging researchers often use them to identify formation mineral compositions, determine formation lithology combinations, analyze pore fluid properties, select interpretation models and parameters, calculate formation geological parameters, verify interpretation results, and evaluate formations, etc. They have a very wide range of uses and have become a powerful tool for log interpretation and data processing.

[0003] Currently, in the identification of oil and gas layers, first, the target formation for log interpretation and evaluation needs to be determined. Then, a log interpretation crossplot is established based on relevant data such as logging and well testing for the target formation. Currently, the technology can be created through manual tools or through professional software. After the log interpretation chart is created, the characteristic values of the logging curves of the target formation are plotted on the log interpretation chart. Then, in an artificial way, based on the position of the plotted characteristic values of this formation on the log interpretation chart and the professional knowledge of researchers, a comprehensive analysis is carried out to obtain the identification conclusion of the oil and gas layer. Repeating this process, after interpreting one oil and gas layer, the identification conclusion of the next section of the oil and gas layer is identified. It can be seen that the current method for identifying oil and gas layers requires researchers to manually interpret layer by layer and cannot perform intelligent batch processing, resulting in low identification efficiency. Therefore, how to achieve automatic identification of oil and gas layers to improve the identification efficiency has become an urgent problem to be solved. Summary of the Invention

[0004] In view of this, the purpose of the present application is to provide a method, device, electronic device, and storage medium for identifying oil and gas layers, which can project logging characteristic values into a log interpretation crossplot and, based on the projection position and pre-created identification rules, determine the identification result of the oil and gas layer of the reservoir represented by the projection position, enabling intelligent batch processing without the need for researchers to manually interpret layer by layer, and improving the efficiency of identifying oil and gas layers.

[0005] The present application mainly includes the following aspects:

[0006] In a first aspect, an embodiment of the present application provides a method for identifying an oil and gas layer, where the identification method includes:

[0007] Obtain a pre-created log interpretation crossplot;

[0008] Obtain logging characteristic values according to the data sources corresponding to the horizontal and vertical coordinates in the log interpretation crossplot;

[0009] Project the logging eigenvalue onto the logging interpretation crossplot to obtain the projection position of the logging eigenvalue in the logging interpretation crossplot;

[0010] Based on the projection position and the pre-created identification rule, determine the oil and gas layer identification result of the reservoir represented by the projection position.

[0011] Further, the step of determining the oil and gas layer identification result of the reservoir represented by the projection position based on the projection position and the pre-created identification rule includes:

[0012] Based on the projection position, determine the distance between the projection position and each identification line in the logging interpretation crossplot;

[0013] Determine the identification line corresponding to the minimum distance among the distances as the target identification line, and determine the geometric relationship between the projection position and the target identification line;

[0014] Determine the target conclusion corresponding to the geometric relationship in the pre-created identification rule, and determine the target conclusion as the oil and gas layer identification result of the reservoir represented by the projection position.

[0015] Further, create a logging interpretation crossplot through the following steps:

[0016] Obtain crossplot parameters; wherein, the crossplot parameters include crossplot type, abscissa name, ordinate name, data source, coordinate type, and scale range;

[0017] Use the crossplot parameters to create a logging interpretation crossplot.

[0018] Further, create an identification rule through the following steps:

[0019] According to the data sources corresponding to the abscissa and ordinate in the logging interpretation crossplot, obtain logging eigenvalues and the oil testing conclusion label data corresponding to the logging eigenvalues;

[0020] Project the logging eigenvalues and the oil testing conclusion label data corresponding to the logging eigenvalues onto the logging interpretation crossplot to obtain oil testing conclusion projection points;

[0021] Based on the oil testing conclusion projection points, obtain the identification lines of different reservoirs in the logging interpretation crossplot;

[0022] Based on the oil testing conclusion projection points and the identification lines, determine the geometric relationship between the oil testing conclusion projection points and the identification lines by the vector method;

[0023] For each geometric relationship, determine the target conclusion corresponding to each geometric relationship;

[0024] Determine the mapping relationship between each geometric relationship and the target conclusion as the recognition rule.

[0025] Furthermore, the step of determining the target conclusion corresponding to each geometric relationship for each geometric relationship includes:

[0026] If the geometric relationship between the test oil conclusion projection point and the identification line is that the test oil conclusion projection point is on the first side of the first identification line, then determine the oil and gas layer identification result of the reservoir represented by the test oil conclusion projection point as an oil layer as the target conclusion corresponding to the geometric relationship;

[0027] If the geometric relationship between the test oil conclusion projection point and the identification line is that the test oil conclusion projection point is on the second side of the first identification line and the test oil conclusion projection point is on the first side of the second identification line, then determine the oil and gas layer identification result of the reservoir represented by the test oil conclusion projection point as an oil-water layer as the target conclusion corresponding to the geometric relationship;

[0028] If the geometric relationship between the test oil conclusion projection point and the identification line is that the test oil conclusion projection point is on the second side of the second identification line, then determine the oil and gas layer identification result of the reservoir represented by the test oil conclusion projection point as a water layer as the target conclusion corresponding to the geometric relationship.

[0029] Furthermore, the recognition method further includes:

[0030] Obtain updated data, where the updated data includes at least one of logging characteristic values and test oil conclusion label data corresponding to the logging characteristic values;

[0031] Update the logging interpretation crossplot and the recognition rule through the updated data.

[0032] Furthermore, the logging characteristic values are obtained through the following steps:

[0033] For each well, determine whether the reservoir of the well has been divided;

[0034] If so, extract the logging characteristic values according to the reservoir divided by the well;

[0035] If not, use the activity method to determine the formation interface of the well, and determine the reservoir and non-reservoir according to the shale content of the formation interface, eliminate the non-reservoir, and extract the logging characteristic values of the reservoir.

[0036] In a second aspect, an embodiment of the present application further provides an oil and gas layer identification device, where the identification device includes:

[0037] A first acquisition module, configured to acquire a pre-created logging interpretation crossplot;

[0038] A second acquisition module, configured to acquire logging characteristic values according to data sources corresponding to the horizontal and vertical coordinates in the logging interpretation cross-plot

[0039] A projection module, configured to project the logging characteristic values onto the logging interpretation cross-plot to obtain the projection positions of the logging characteristic values in the logging interpretation cross-plot

[0040] An identification module, configured to determine the oil and gas layer identification result of the reservoir represented by the projection position based on the projection position and a pre-created identification rule

[0041] In a third aspect, an embodiment of the present application further provides an electronic device, including: a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device runs, the processor communicates with the memory through the bus. When the machine-readable instructions are executed by the processor, the steps of the above-mentioned oil and gas layer identification method are executed.

[0042] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium. A computer program is stored on the computer-readable storage medium. When the computer program is run by a processor, the steps of the above-mentioned oil and gas layer identification method are executed.

[0043] An oil and gas layer identification method, device, electronic device, and storage medium provided by an embodiment of the present application. The identification method includes: acquiring a pre-created logging interpretation cross-plot; acquiring logging characteristic values according to data sources corresponding to the horizontal and vertical coordinates in the logging interpretation cross-plot; projecting the logging characteristic values onto the logging interpretation cross-plot to obtain the projection positions of the logging characteristic values in the logging interpretation cross-plot; and determining the oil and gas layer identification result of the reservoir represented by the projection position based on the projection position and a pre-created identification rule.

[0044] In this way, by adopting the technical solution provided by the present application, it is possible to project logging characteristic values onto a logging interpretation cross-plot, and based on the projection position and a pre-created identification rule, determine the oil and gas layer identification result of the reservoir represented by the projection position, enabling intelligent batch processing without manual layer-by-layer interpretation by researchers, thereby improving the efficiency of oil and gas layer identification.

[0045] To make the above objects, features, and advantages of the present application more obvious and understandable, the following specifically enumerates preferred embodiments and, in conjunction with the accompanying drawings, provides detailed descriptions as follows. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] To more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the accompanying drawings required for the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation of the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0047] Figure 1 Shows the flowchart of a method for identifying oil and gas layers provided by the embodiments of the present application;

[0048] Figure 2 Shows the flowchart of another method for identifying oil and gas layers provided by the embodiments of the present application;

[0049] Figure 3 Shows the schematic diagram of the geometric relationship between points and lines in space provided by the embodiments of the present application;

[0050] Figure 4 Shows the schematic diagram of establishing an interpretation standard provided by the embodiments of the present application;

[0051] Figure 5 Shows the schematic diagram of the discrimination rule for identifying oil and gas layers based on the interpretation standard provided by the embodiments of the present application;

[0052] Figure 6 Shows the schematic diagram of the process for identifying oil and gas layers provided by the embodiments of the present application;

[0053] Figure 7 Shows one of the structural schematic diagrams of an apparatus for identifying oil and gas layers provided by the embodiments of the present application;

[0054] Figure 8 Shows another structural schematic diagram of an apparatus for identifying oil and gas layers provided by the embodiments of the present application;

[0055] Figure 9 Shows the structural schematic diagram of an electronic device provided by the embodiments of the present application. Detailed implementation manners

[0056] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of this application. It should be understood that the accompanying drawings in this application are only for the purposes of illustration and description, and are not used to limit the protection scope of this application. In addition, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowchart may not be implemented in sequence, and steps without a logical context relationship may be reversed or implemented simultaneously. In addition, those skilled in the art may add one or more other operations to the flowchart or remove one or more operations from the flowchart under the guidance of the content of this application.

[0057] In addition, the described embodiments are only some embodiments of this application, rather than all embodiments. The components of the embodiments of this application usually described and illustrated in the accompanying drawings here may be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of this application claimed, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative efforts fall within the protection scope of this application.

[0058] To enable those skilled in the art to use the content of this application, the following implementation manners are given in combination with a specific application scenario, "identification of oil and gas layers". For those skilled in the art, without departing from the spirit and scope of this application, the general principles defined here can be applied to other embodiments and application scenarios.

[0059] The following methods, devices, electronic devices, or computer-readable storage media in the embodiments of this application can be applied to any scenario that requires the identification of oil and gas layers. The embodiments of this application do not limit the specific application scenario. Any solution that uses the method, device, electronic device, and storage media for identifying an oil and gas layer provided in the embodiments of this application falls within the protection scope of this application.

[0060] Based on this, this application proposes a method, device, electronic device, and storage media for identifying an oil and gas layer. The identification method includes: obtaining a pre-created well logging interpretation crossplot; obtaining well logging characteristic values according to the data sources corresponding to the horizontal and vertical coordinates in the well logging interpretation crossplot; projecting the well logging characteristic values into the well logging interpretation crossplot to obtain the projection positions of the well logging characteristic values in the well logging interpretation crossplot; and determining the oil and gas layer identification result of the reservoir represented by the projection positions based on the projection positions and a pre-created identification rule.

[0061] In this way, by adopting the technical solution provided by this application, the logging characteristic values can be projected onto the logging interpretation crossplot, and based on the projection position and the pre-created identification rules, the oil and gas layer identification result of the reservoir represented by the projection position can be determined. Without the need for researchers to manually interpret layer by layer, intelligent batch processing can be carried out, improving the efficiency of oil and gas layer identification.

[0062] To facilitate the understanding of the embodiments of this application, a method for identifying oil and gas layers disclosed in the embodiments of this application will be introduced in detail first.

[0063] Please refer to Figure 1 , Figure 1 which is a flowchart of a method for identifying oil and gas layers provided by the embodiments of this application. As shown in Figure 1 , the identification method includes:

[0064] S101. Obtain a pre-created logging interpretation crossplot;

[0065] It should be noted that the logging interpretation crossplot is created through the following steps:

[0066] I. Obtain the crossplot parameters;

[0067] In this step, the crossplot parameters include the crossplot type, the name of the abscissa, the name of the ordinate, the data source, the coordinate type, and the scale range.

[0068] II. Use the crossplot parameters to create a logging interpretation crossplot.

[0069] In this step, through the above crossplot parameters, an online creation of the logging interpretation crossplot can be carried out using a mapping tool.

[0070] Exemplarily, an online creation of a logging interpretation crossplot of acoustic travel time and resistivity is carried out. The crossplot type is acoustic travel time - resistivity; the crossplot dimension is two - dimensional; the crossplot category belongs to the electrical property crossplot; the abscissa is acoustic travel time, the data source is taken from the logging curve, the coordinate type is linear coordinate, and the scale interval is adaptive; the ordinate is resistivity, the data source is taken from the logging curve, the coordinate type is linear coordinate, and the scale interval is adaptive.

[0071] S102. Obtain logging characteristic values according to the data sources corresponding to the abscissa and ordinate in the logging interpretation crossplot;

[0072] In this step, the data source is the logging curve. Stratified values are taken from the logging curve. For wells where the reservoir has been divided, automatic values are taken according to the divided reservoir sections; for wells where the formation has not been divided, the general activity method is used for automatic formation division.

[0073] It should be noted that the logging characteristic values are obtained through the following steps:

[0074] 1], for each well, determine whether the reservoir has been divided for the well;

[0075] 2], if yes, then extract the logging characteristic value according to the reservoir divided by the well;

[0076] 3] If not, the activity method is used to determine the formation interface of the well, and the reservoir and non-reservoir are determined according to the mud content of the formation interface, the non-reservoir is eliminated, and the logging characteristic value of the reservoir is extracted.

[0077] In the above steps 1] to 3], the calculation formula for the activity discrete form of the logging curve is:

[0078]

[0079]

[0080] Where, E(H0) represents the activity value of the logging curve at point H0; L represents the window length used to calculate the activity; represents the average value of the logging curve within the range of L / 2 above and below the H0 point; N represents the number of sampling points of the discrete logging curve within the window length L; K i (H) represents the sampling value of the i-th point on the logging curve. Select a suitable logging curve and window length, calculate the activity point by point according to the above formula, and obtain the activity curve of the logging curve. Determine the formation interface according to the relative maximum value on the activity curve, and preliminarily define the reservoir and non-reservoir according to the mud content, such as the limit of 40% (configurable). When interpreting the logging, it is necessary to exclude the non-reservoir and only take values ​​for the reservoir section.

[0081] S103, projecting the well logging characteristic value onto the well logging interpretation cross chart to obtain a projection position of the well logging characteristic value on the well logging interpretation cross chart;

[0082] S104: Determine an oil and gas layer identification result of the reservoir represented by the projection position based on the projection position and a pre-created identification rule.

[0083] In step S103 to step S104, batch intelligent interpretation is performed based on the established interpretation standard (identification rule). The drawing board is called to pick up the logging value of a single reservoir or multiple reservoirs. The characteristic value of the logging curve will be automatically projected on the intersection diagram. According to the position of the projection point on the intersection diagram and the established interpretation standard, the interpretation conclusion of each layer (oil and gas layer identification result) is intelligently determined, and the interpretation conclusion can be fed back and displayed on the logging diagram.

[0084] It should be noted that the identification rules are created through the following steps:

[0085] 1), Obtain logging characteristic values and the test oil conclusion label data corresponding to the logging characteristic values according to the data sources corresponding to the horizontal and vertical coordinates in the logging interpretation crossplot;

[0086] 2), Project the logging characteristic values and the test oil conclusion label data corresponding to the logging characteristic values onto the logging interpretation crossplot to obtain the test oil conclusion projection points;

[0087] 3), Based on the test oil conclusion projection points, obtain the identification lines of different reservoirs in the logging interpretation crossplot;

[0088] 4), Based on the test oil conclusion projection points and the identification lines, determine the geometric relationship between the test oil conclusion projection points and the identification lines by the vector method;

[0089] 5), For each geometric relationship, determine the target conclusion corresponding to each geometric relationship;

[0090] In the above steps 1) to 5), the interpretation standard is established intelligently. The interpretation standard is established intelligently through horizon data, logging characteristic values, and test oil layer labels. Here, the horizon data is the reservoir name, such as Chang 2-1 horizon, Chang 2-2 horizon; the logging characteristic values are the logging curve values, such as resistivity curve value, acoustic travel time curve value; the test oil layer label is the test oil conclusion, such as oil layer, water layer. Obtain the logging characteristic values and the test oil conclusion crossplot data (i.e., the test oil conclusion label data, such as conclusion data of oil layer, water layer, oil-water mixed layer, etc.) according to the data sources corresponding to the horizontal and vertical coordinates configured in the crossplot, and perform online projection of the test oil labels. After projection, the logging interpreter draws the identification lines according to the conclusion areas of oil, gas, and water layers, and then intelligently establishes the interpretation standard according to the spatial relationship between the test oil conclusion projection points and the identification lines.

[0091] As an example, please refer to Figure 3 , Figure 3 which is a schematic diagram of the geometric relationship between a point and a line in space provided by an embodiment of the present application. As shown in Figure 3 , it can be determined whether point P is on the left or right side of vector AB according to the geometric meaning of the cross product result r of vector AB and vector AP. r represents the geometric meaning of vector cross product. If r>0, then point P is on the left side of vector AB; if r = 0, then point P is on vector AB; if r<0, then point P is on the right side of vector AB.

[0092] It should be noted that the step of determining the target conclusion corresponding to each geometric relationship for each geometric relationship includes:

[0093] (1), If the geometric relationship between the test oil conclusion projection point and the identification line is that the test oil conclusion projection point is on the first side of the first identification line, then determine that the oil and gas layer identification result of the reservoir represented by the test oil conclusion projection point as an oil layer is the target conclusion corresponding to the geometric relationship;

[0094] (2) If the geometric relationship between the test oil conclusion projection point and the identification line is that the test oil conclusion projection point is on the second side of the first identification line and the test oil conclusion projection point is on the first side of the second identification line, then determine the oil and water layer identification result of the reservoir represented by the test oil conclusion projection point as the target conclusion corresponding to the geometric relationship;

[0095] (3) If the geometric relationship between the test oil conclusion projection point and the identification line is that the test oil conclusion projection point is on the second side of the second identification line, then determine the water layer identification result of the reservoir represented by the test oil conclusion projection point as the target conclusion corresponding to the geometric relationship.

[0096] For example, refer to Figure 4 , Figure 4 which is a schematic diagram for establishing an interpretation standard provided by an embodiment of the present application. As shown in Figure 4 , in the figure, the dark circular projection points represent that the oil and gas layer identification conclusion is an oil layer, the light circular projection points represent that the oil and gas layer identification conclusion is an oil-water layer, and the triangular projection points represent that the oil and gas layer identification conclusion is a water layer; ①-⑥ represent the line segment numbers of the identification lines; the vector line direction setting represents the default vector direction rule of each identification line in the chart. According to the vector method, judge the geometric relationship between the point in the regional space and the identification line. The oil layer area is on the left side of line segment ①, on the left side of line segment ②, and on the left side of line segment ③. The oil-water layer area (light circular projection points) and the water layer area (triangular projection points) are established with the same principle as above.

[0097] 6) Determine the mapping relationship between each geometric relationship and the target conclusion as the identification rule.

[0098] In this step, referring to the above example, the identification rule for the oil and gas layers of this chart is: Oil layer (target conclusion): Left side of identification lines ①-②-③ (geometric relationship); Oil-water layer (target conclusion): Right side of identification lines ①-②-③, left side of identification lines ④-⑤-⑥ (geometric relationship); Water layer (target conclusion): Right side of identification lines ④-⑤-⑥ (geometric relationship).

[0099] It should be noted that please refer to Figure 2 , Figure 2 which is a flowchart of another oil and gas layer identification method provided by an embodiment of the present application. As shown in Figure 2 , in the figure, the steps of determining the oil and gas layer identification result of the reservoir represented by the projection position based on the projection position and the pre-created identification rule include:

[0100] S201. Based on the projection position, determine the distance between the projection position and each identification line in the logging interpretation crossplot.

[0101] S202. Determine the identification line corresponding to the smallest distance among the distances as the target identification line, and determine the geometric relationship between the projection position and the target identification line;

[0102] S203. Determine the target conclusion corresponding to the geometric relationship in the pre-created recognition rules, and determine the target conclusion as the oil and gas layer identification result of the reservoir represented by the projection position.

[0103] In the above steps S201 to S203, it is a step of batch intelligent interpretation based on the established interpretation criteria. Call the chart, pick up the logging values of single reservoirs and multiple reservoirs. The characteristic values of the logging curves will be automatically projected on the cross plot. According to the position of the projection point on the cross plot and the established interpretation criteria, the interpretation conclusion of each layer is intelligently determined, and the obtained interpretation conclusion is fed back and displayed on the logging chart. Here, when performing logging interpretation, call the saved interpretation criteria, take values layer by layer through the activity method or automatically take values based on the existing layer segments. After taking values, batch process and intelligently identify the area where the characteristic values of each interpreted layer segment are located in the criteria according to the geometric relationship determination rules saved in the horizon criteria, and automatically give the interpretation conclusion of each interpreted layer segment.

[0104] As an example, please refer to Figure 5 , Figure 5 which is a schematic diagram of the oil and gas layer identification and discrimination rules based on the interpretation criteria provided by the embodiment of the present application. As shown in Figure 5 , taking the projection point A in the figure as an example, when the system performs intelligent interpretation on the identification of the oil and gas layer of the reservoir it represents, it automatically calculates and discriminates. The discrimination algorithm is as follows: First, the system makes a distance judgment from this projection point A to each identification line, and takes the identification line with the shortest distance as the evaluation basis, and then obtains the geometric relationship with this identification line. Furthermore, it makes a correlation comparison with the interpretation criteria of this chart plate to obtain the closest conclusion in the criteria. In this example, there are 2 identification lines, namely ①-②-③ and ④-⑤-⑥. Each identification line has 3 line segments. Taking ①-②-③ as an example, make perpendicular lines from the projection point A to the 3 line segments to judge the distance. When the perpendicular line falls on the extension line of the line segment, connect the projection point to the two endpoints of this line segment, and take the shortest one as the judgment distance from the projection point to this line segment. In this example, they are R1, R2, and R3 respectively. Therefore, the final discrimination basis of the projection point A and the identification line ①-②-③ is the geometric relationship between the projection point A and the line segment ②. It can be seen from the figure that the projection point A is on the left side of the identification line ①-②-③; similarly, it can be obtained that the projection point A is on the left side of the identification line ④-⑤-⑥; when the projection point is on the same side of the two identification lines, further compare the shortest distances from the projection point to the two identification lines. In this example, R2 < R5. Therefore, the final intelligent identification result of this projection point A is: the projection point A is on the left side of the identification line ①-②-③. According to the intelligent identification result of this projection point and the interpretation criteria for comparison, the interpretation criteria of this example are as shown in Figure 4, Oil layer: to the left of the identification line ①-②-③; Oil-water transition zone: to the right of the identification line ①-②-③ and to the left of the identification line ④-⑤-⑥; Water layer: to the right of the identification line ④-⑤-⑥. Therefore, the reservoir represented by the projection point A is identified as an oil layer.

[0105] According to the above algorithm, the projection point can be automatically valued, the position of the projection point can be automatically judged, and based on the position of the projection point and the interpretation criteria, the identification conclusions of multiple reservoir sections for oil and gas layers can be given batchwise and intelligently.

[0106] It should be noted that the identification method also includes:

[0107] ①. Obtain updated data, where the updated data includes at least one of logging characteristic values and the test oil conclusion label data corresponding to the logging characteristic values;

[0108] ②. Update the logging interpretation crossplot and the identification rules through the updated data.

[0109] In the above steps ① to ②, it is the process of crossplot / interpretation criteria management and iteration. After the crossplot and interpretation criteria are established, the crossplot and its interpretation criteria can be saved, and when saving, they can be associated with the block, horizon, and crossplot type for standardized management and convenient call. After the crossplot / interpretation criteria are saved, they can be edited again. By further supplementing and adjusting the logging characteristic values and the test oil conclusion label data, the crossplot and interpretation criteria can be continuously optimized to achieve continuous iterative update.

[0110] It should be noted that the identification method further includes: conducting fine manual interpretation based on the interactive analysis of well logging diagrams and charts. Combining the manual picking of characteristic values of reservoir well logging curves (single reservoir, multiple reservoirs) and projecting them onto the crossplot chart; and manually picking the projection points on the crossplot chart, which can be single-point picking, multi-point (area, multiple selection) picking, and automatically removing the tested oil layers and projecting them onto the well logging profile diagram. The final interpretation conclusion is determined based on the mutual relationship between these points and the interpretation criteria, the response characteristics of well logging curves, and manual interpretation experience. For example, in a well logging diagram, a depth section is selected, and then according to the horizontal and vertical coordinate parameters of the crossplot chart, the characteristic values of the corresponding curves at this depth section are picked. Single-point projection of the average characteristic values can be performed, that is, the average values of the characteristic values of the curves corresponding to the horizontal and vertical coordinates of the crossplot chart within this depth section are calculated respectively, and then the intersection point of the average values of the horizontal and vertical coordinates is projected onto the crossplot chart; or projection of the characteristic values can be performed, that is, the intersection points of the characteristic values of the curves corresponding to the horizontal and vertical coordinate parameters of the crossplot chart at each discrete depth point within this depth section are all projected onto the crossplot chart. The projection points on the crossplot chart will record the well information, depth information, horizontal and vertical coordinate characteristic value information, and projection information corresponding to the projection points. Here, single-point information can be picked, and based on the well number, depth data, curve characteristic value data, projection point method data, etc. recorded by this projection point, the curve depth section represented by this point can be projected onto the well logging diagram; or an area of the crossplot chart can be drawn to perform multi-point picking. According to the multi-projection point information (automatically removing the projection points of the tested oil layers) within this area, such as well number, depth data, curve characteristic value data, projection point method data, etc., for the multi-point picking situation, the depths represented by the multi-points are automatically merged to obtain the depth section represented by the multi-points, and the curve segments represented by the multiple picked projection points are projected back and displayed on the well logging diagram.

[0111] For example, when conducting further analysis with human participation on the interpretation section of 2167.25m - 2173.75m, real-time value taking is performed on this section in the well logging profile diagram, and the obtained characteristic values of acoustic time difference and resistivity are projected onto the called chart in real time. According to the area where the new projection point is located, the corresponding oil and gas layer identification conclusion can be obtained and can be manually adjusted.

[0112] It should be noted that in the prior art, the target layer for logging interpretation and evaluation must first be determined, and then a logging interpretation intersection chart is established for the logging, oil testing and other related data of the target layer. The current technology can be created through manual tools or professional software. After the logging interpretation chart is created, the logging curve characteristic value of the target layer is projected onto the logging interpretation chart. Then, the oil and gas layer identification conclusion is obtained by manually analyzing the position of the logging characteristic value of this layer on the logging interpretation chart combined with the professional knowledge of the researchers. This is repeated. After interpreting one oil and gas layer, the interpretation conclusion of the next oil and gas layer is identified. However, the above method has the following shortcomings: (1) The interpretation chart and the logging interpretation profile are relatively isolated from each other, and the efficiency of the fusion application of the two is low, which needs to be strengthened. (2) The application of the interpretation chart can only assist researchers in manually interpreting each layer, and cannot be intelligently processed in batches. (3) The iteration of the interpretation chart is not highly targeted, which is very unfavorable to the precipitation and reuse of the results and knowledge formed. Therefore, in the current process of fine logging interpretation, it is not possible to well implement interactive analysis from logging curve values ​​to crossplot projection and combined with crossplot values ​​to logging curve projection. In order to solve the problem of difficulty in interactive interpretation between logging interpretation crossplot and logging curve, as well as the problem of intelligent batch interpretation of multi-layer segments based on plate interpretation, rapid creation of plates, establishment of interpretation standards, standardized management of plates and iterative updates, this embodiment proposes a method for identifying oil and gas layers. Figure 6 , Figure 6 A schematic diagram of a process for identifying oil and gas layers provided in an embodiment of the present application is as follows: Figure 6 As shown, this embodiment creates a plate, establishes an interpretation standard, manages and iterates the plate / interpretation standard to update the plate / interpretation standard, then performs layered value extraction of the well logging curve, calls the plate / interpretation standard for intelligent batch interpretation, and can also perform fine manual interpretation, and perform linkage analysis of the well logging map and the intersection map, such as projecting the well logging map to the intersection map and the intersection map to the well logging map, so as to draw conclusions on oil and gas layer identification. Through this embodiment, the following effects can be achieved: (1) The linkage and interactive analysis of the plate and the well logging profile map in the well logging interpretation evaluation can be realized, which effectively assists the research in fine manual interpretation. (2) Intelligent and batch interpretation based on interpretation standards can be realized, which greatly reduces the workload of well logging interpretation evaluation and improves work efficiency; and the subjective influence of interpreters can be reduced through standards. (3) It can provide online establishment of well logging interpretation plates and interpretation standards, and perform unified storage management and support iterative re-editing, which is conducive to improving the sedimentation and reuse of results and knowledge.

[0113] A method for identifying an oil and gas layer provided by an embodiment of the present application, the identification method comprising: obtaining a pre-created logging interpretation cross-plot; obtaining logging characteristic values according to data sources corresponding to the horizontal and vertical coordinates in the logging interpretation cross-plot; projecting the logging characteristic values into the logging interpretation cross-plot to obtain a projection position of the logging characteristic values in the logging interpretation cross-plot; and determining an oil and gas layer identification result of a reservoir represented by the projection position based on the projection position and a pre-created identification rule.

[0114] In this way, by adopting the technical solution provided by the present application, the logging characteristic values can be projected into the logging interpretation cross-plot, and based on the projection position and the pre-created identification rule, the oil and gas layer identification result of the reservoir represented by the projection position can be determined. There is no need for researchers to manually interpret layer by layer, and intelligent batch processing can be carried out, improving the efficiency of identifying oil and gas layers.

[0115] Based on the same inventive concept, an embodiment of the present application further provides an oil and gas layer identification device corresponding to the above-mentioned oil and gas layer identification method. Since the principle of solving problems by the device in the embodiment of the present application is similar to that of the above-mentioned method in the embodiment of the present application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.

[0116] Please refer to Figure 7 、 Figure 8 , Figure 7 which is one of the structural schematic diagrams of an oil and gas layer identification device provided by an embodiment of the present application, Figure 8 which is the second structural schematic diagram of an oil and gas layer identification device provided by an embodiment of the present application. As shown in Figure 7 , the identification device 710 includes:

[0117] A first acquisition module 711, configured to acquire a pre-created logging interpretation cross-plot;

[0118] A second acquisition module 712, configured to acquire logging characteristic values according to data sources corresponding to the horizontal and vertical coordinates in the logging interpretation cross-plot;

[0119] A projection module 713, configured to project the logging characteristic values into the logging interpretation cross-plot to obtain a projection position of the logging characteristic values in the logging interpretation cross-plot;

[0120] An identification module 714, configured to determine an oil and gas layer identification result of a reservoir represented by the projection position based on the projection position and a pre-created identification rule.

[0121] Optionally, the identification module 714 is specifically configured to:

[0122] Based on the projection position, determine the distances between the projection position and each identification line in the logging interpretation crossplot;

[0123] Determine the identification line corresponding to the minimum distance among the distances as the target identification line, and determine the geometric relationship between the projection position and the target identification line;

[0124] Determine the target conclusion corresponding to the geometric relationship in the pre-created identification rules, and determine the target conclusion as the oil and gas layer identification result of the reservoir represented by the projection position.

[0125] Optionally, as Figure 8 shown, the identification device 710 further includes a creation module 715, and the creation module 715 is configured to:

[0126] Obtain crossplot parameters; wherein, the crossplot parameters include crossplot type, abscissa name, ordinate name, data source, coordinate type, and scale range;

[0127] Create a logging interpretation crossplot by using the crossplot parameters.

[0128] Optionally, as Figure 8 shown, the identification device 710 further includes a construction module 716, and the construction module 716 is configured to:

[0129] According to the data sources corresponding to the abscissa and ordinate in the logging interpretation crossplot, obtain logging characteristic values and the test oil conclusion label data corresponding to the logging characteristic values;

[0130] Project the logging characteristic values and the test oil conclusion label data corresponding to the logging characteristic values onto the logging interpretation crossplot to obtain test oil conclusion projection points;

[0131] Based on the test oil conclusion projection points, obtain the identification lines of different reservoirs in the logging interpretation crossplot;

[0132] Based on the test oil conclusion projection points and the identification lines, determine the geometric relationship between the test oil conclusion projection points and the identification lines by the vector method;

[0133] For each geometric relationship, determine the target conclusion corresponding to each geometric relationship;

[0134] Determine the mapping relationship between each geometric relationship and the target conclusion as the identification rules.

[0135] Optionally, when the construction module 716 is used to determine the target conclusion corresponding to each geometric relationship for each geometric relationship, the construction module 716 is specifically configured to:

[0136] If the geometric relationship between the oil test conclusion point and the identification line is that the oil test conclusion point is on the first side of the first identification line, the oil and gas layer identification result of the reservoir represented by the oil test conclusion point is determined as the oil layer as the target conclusion corresponding to the geometric relationship;

[0137] If the geometric relationship between the oil test conclusion point and the identification line is that the oil test conclusion point is on the second side of the first identification line, and the oil test conclusion point is on the first side of the second identification line, then the oil and gas layer identification result of the reservoir represented by the oil test conclusion point is that the oil and water are in the same layer, which is determined as the target conclusion corresponding to the geometric relationship;

[0138] If the geometric relationship between the oil test conclusion point and the identification line is that the oil test conclusion point is on the second side of the second identification line, the oil and gas layer identification result of the reservoir represented by the oil test conclusion point is determined as a water layer as the target conclusion corresponding to the geometric relationship.

[0139] Optional, such as Figure 8 As shown, the identification device 710 further includes an updating module 717, and the updating module 717 is used to:

[0140] Acquire update data, wherein the update data includes at least one of a well logging characteristic value and oil test conclusion label data corresponding to the well logging characteristic value;

[0141] The logging interpretation intersection diagram and identification rules are updated through the updated data.

[0142] Optionally, the second acquisition module 712 is specifically used for:

[0143] For each well, determine whether the reservoir has been partitioned for the well;

[0144] If yes, then the well logging characteristic values ​​are extracted according to the reservoir divided by the well;

[0145] If not, the activity method is used to determine the formation interface of the well, and the reservoir and non-reservoir are determined according to the mud content of the formation interface, the non-reservoir is eliminated, and the logging characteristic value of the reservoir is extracted.

[0146] An embodiment of the present application provides an oil and gas layer identification device, which includes: a first acquisition module, used to acquire a pre-created well logging interpretation intersection map; a second acquisition module, used to acquire well logging characteristic values ​​according to the data sources corresponding to the horizontal and vertical coordinates in the well logging interpretation intersection map; a projection module, used to project the well logging characteristic values ​​into the well logging interpretation intersection map to obtain the projection position of the well logging characteristic values ​​in the well logging interpretation intersection map; and an identification module, used to determine the oil and gas layer identification result of the reservoir represented by the projection position based on the projection position and a pre-created identification rule.

[0147] In this way, by adopting the technical solution provided by the present application, the logging characteristic values can be projected onto the logging interpretation crossplot, and based on the projection position and the pre-created recognition rules, the oil and gas layer recognition result of the reservoir represented by the projection position can be determined. Without the need for researchers to manually interpret layer by layer, intelligent batch processing can be carried out, improving the efficiency of oil and gas layer recognition.

[0148] Please refer to Figure 9 , Figure 9 which is a schematic structural diagram of an electronic device provided by an embodiment of the present application. As Figure 9 shown in

[0149] the electronic device 900 includes a processor 910, a memory 920, and a bus 930. Figures 1 to 2 The memory 920 stores machine-readable instructions executable by the processor 910. When the electronic device 900 runs, the processor 910 communicates with the memory 920 through the bus 930. When the machine-readable instructions are executed by the processor 910, the steps of the oil and gas layer recognition method in the method embodiment as shown above

[0150] can be executed. For the specific implementation manner, reference can be made to the method embodiment, which will not be elaborated here. Figures 1 to 2 An embodiment of the present application also provides a computer-readable storage medium. A computer program is stored on the computer-readable storage medium. When the computer program is run by a processor, the steps of the oil and gas layer recognition method in the method embodiment as shown above

[0151] can be executed. For the specific implementation manner, reference can be made to the method embodiment, which will not be elaborated here.

[0152] Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the foregoing method embodiments, which will not be elaborated here.

[0153] The unit described as a separation component may or may not be physically separated. The component shown as a unit may or may not be a physical unit, that is, it may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0154] In addition, each functional unit in various embodiments of the present application may be integrated into a processing unit, may exist separately as individual physical units, or two or more units may be integrated into one unit.

[0155] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium executable by a processor. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0156] Finally, it should be noted that the above-described embodiments are only specific implementation manners of the present application, used to illustrate the technical solutions of the present application, and are not intended to limit them. The protection scope of the present application is not limited thereto. Although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: any person skilled in the art within the technical scope disclosed by the present application can still modify the technical solutions described in the foregoing embodiments, or can easily think of changes, or perform equivalent replacements on some of the technical features; and these modifications, changes, or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for identifying oil and gas reservoirs, characterized in that, the identification method includes: Obtain a pre-created logging interpretation crossplot; According to the data sources corresponding to the horizontal and vertical coordinates in the logging interpretation crossplot, obtain logging characteristic values; Project the logging characteristic values onto the logging interpretation crossplot to obtain the projection position of the logging characteristic values in the logging interpretation crossplot; Based on the projection position and a pre-created identification rule, determine the oil and gas reservoir identification result of the reservoir represented by the projection position.

2. The identification method according to claim 1, characterized in that, the step of determining the oil and gas reservoir identification result of the reservoir represented by the projection position based on the projection position and a pre-created identification rule includes: Based on the projection position, determine the distance between the projection position and each identification line in the logging interpretation crossplot; Determine the identification line corresponding to the smallest distance among the distances as the target identification line, and determine the geometric relationship between the projection position and the target identification line; Determine the target conclusion corresponding to the geometric relationship in the pre-created identification rule, and determine the target conclusion as the oil and gas reservoir identification result of the reservoir represented by the projection position.

3. The identification method according to claim 1, characterized in that, Create a logging interpretation crossplot through the following steps: Obtain crossplot parameters; wherein, the crossplot parameters include crossplot type, horizontal coordinate name, vertical coordinate name, data source, coordinate type, and scale range; Use the crossplot parameters to create a logging interpretation crossplot.

4. The identification method according to claim 1, characterized in that, Create an identification rule through the following steps: According to the data sources corresponding to the horizontal and vertical coordinates in the logging interpretation crossplot, obtain logging characteristic values and the oil testing conclusion label data corresponding to the logging characteristic values; Project the logging characteristic values and the oil testing conclusion label data corresponding to the logging characteristic values onto the logging interpretation crossplot to obtain oil testing conclusion projection points; Based on the oil testing conclusion projection points, obtain the identification lines of different reservoirs in the logging interpretation crossplot; Based on the oil testing conclusion projection points and the identification lines, determine the geometric relationship between the oil testing conclusion projection points and the identification lines by the vector method; For each geometric relationship, determine the target conclusion corresponding to each geometric relationship; Determine the mapping relationship between each geometric relationship and the target conclusion as the identification rule.

5. The identification method according to claim 4, characterized in that, the step of determining the target conclusion corresponding to each geometric relationship for each geometric relationship includes: If the geometric relationship between the oil testing conclusion projection point and the identification line is that the oil testing conclusion projection point is on the first side of the first identification line, then determine the oil and gas reservoir identification result of the reservoir represented by the oil testing conclusion projection point as an oil layer as the target conclusion corresponding to the geometric relationship; If the geometric relationship between the oil testing conclusion projection point and the identification line is that the oil testing conclusion projection point is on the second side of the first identification line and the oil testing conclusion projection point is on the first side of the second identification line, then the oil and gas layer identification result of the reservoir represented by the oil testing conclusion projection point being an oil-water layer is determined as the target conclusion corresponding to the geometric relationship; If the geometric relationship between the oil testing conclusion projection point and the identification line is that the oil testing conclusion projection point is on the second side of the second identification line, then the oil and gas layer identification result of the reservoir represented by the oil testing conclusion projection point being a water layer is determined as the target conclusion corresponding to the geometric relationship.

6. The identification method according to claim 4, characterized in that, the identification method further includes: obtaining updated data, where the updated data includes at least one of well logging characteristic values and oil testing conclusion label data corresponding to the well logging characteristic values; updating the well logging interpretation crossplot and the identification rules through the updated data.

7. The identification method according to claim 1, characterized in that, the well logging characteristic values are obtained through the following steps: For each well, determine whether the reservoir of the well has been divided; If so, extract the well logging characteristic values according to the divided reservoir of the well; If not, use the activity method to determine the formation interface of the well, determine the reservoir and non-reservoir according to the shale content of the formation interface, eliminate the non-reservoir, and extract the well logging characteristic values of the reservoir.

8. An identification device for oil and gas layers, characterized in that, the identification device includes: a first acquisition module for acquiring a pre-created well logging interpretation crossplot; a second acquisition module for acquiring well logging characteristic values according to the data sources corresponding to the horizontal and vertical coordinates in the well logging interpretation crossplot; a projection module for projecting the well logging characteristic values into the well logging interpretation crossplot to obtain the projection position of the well logging characteristic values in the well logging interpretation crossplot; an identification module for determining the oil and gas layer identification result of the reservoir represented by the projection position based on the projection position and the pre-created identification rules.

9. An electronic device, characterized in that, includes: a processor, a memory and a bus, the memory stores machine-readable instructions executable by the processor, when the electronic device runs, the processor communicates with the memory through the bus, and when the machine-readable instructions are run by the processor, the steps of the oil and gas layer identification method according to any one of claims 1 to 7 are executed.

10. A computer-readable storage medium, characterized in that, a computer program is stored on the computer-readable storage medium, and when the computer program is run by a processor, the steps of the oil and gas layer identification method according to any one of claims 1 to 7 are executed.

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