Mudstone identification method and device, electronic equipment and storage medium

Abstract

The application discloses a mudstone identification method and device, electronic equipment and a storage medium. The method comprises the following steps: determining first attribute information of a plurality of position points in a target well log; determining second attribute information of the plurality of position points according to the first attribute information; judging rock states corresponding to the plurality of position points according to the second attribute information of the plurality of position points; and determining whether the target well log contains mudstone according to the rock states corresponding to the plurality of position points. The method judges the rock states of the position points according to the second attribute information, judges whether the target well log contains mudstone according to the rock states, and the introduction of the second attribute information can fully consider the sensitive parameters caused by different lithology in the rock, thereby improving the accuracy of mudstone identification.

Description

Technical Field

[0001] The present invention relates to the field of geological exploration technology, and in particular to a marl identification method, device, electronic equipment and storage medium. Background Art

[0002] The main reservoir rock type in carbonate oil and gas reservoirs is limestone, but some limestones develop into marl due to excessive mud content. The oil and gas storage performance of this type of rock is poor and it is not a favorable reservoir, so it is necessary to be able to accurately identify marl. However, existing technologies usually use rock physics to analyze the sensitive parameters of lithology identification, and obtain the corresponding lithology sensitive parameters through seismic data inversion to complete the lithology identification work based on seismic data. However, the actual data situation is complicated. When the elastic parameters of different lithologies are superimposed together, it is difficult to obtain the lithology sensitive parameters through rock physics analysis, and it is impossible to use the lithology sensitive parameters to distinguish different lithologies. As a result, it becomes particularly difficult to accurately identify and eliminate marl interlayers, which directly restricts the accurate assessment of carbonate reservoir production. Summary of the Invention

[0003] The present invention provides a marl identification method, device, electronic equipment and storage medium to solve the problem of difficulty in identifying marl.

[0004] According to one aspect of the present invention, a method for identifying marl is provided, comprising:

[0005] Determining first attribute information for a plurality of location points in a target well log, the first attribute information being used to characterize how a reflection coefficient of a seismic wave changes with the incident angle of the seismic wave as the seismic wave propagates in a target reservoir; the first attribute information for each location point being how the reflection coefficient of the seismic wave changes with the incident angle of the seismic wave at that location point; the first attribute information comprising an intercept attribute and a gradient attribute; the target well log being a well in the target reservoir for which marl identification is required; and the location point being a point in the target well log;

[0006] Determining second attribute information of a plurality of location points based on the first attribute information of the plurality of location points, wherein the second attribute information of the location points is attribute information for distinguishing the top and bottom interfaces of the marl, constructed based on differences in the first attribute information caused by the marl interlayer at the location points;

[0007] Determining rock states corresponding to the plurality of position points based on the second attribute information of the plurality of position points, wherein the rock states indicate whether the position points are top and bottom interfaces of marl;

[0008] Determine whether the target well contains marl according to the rock states corresponding to the plurality of location points.

[0009] According to another aspect of the present invention, a marl identification device is provided, comprising:

[0010] A first attribute information determination module is configured to determine first attribute information of a plurality of location points within a target well log, wherein the first attribute information is configured to characterize how the reflection coefficient of a seismic wave changes with the incident angle of the seismic wave as the seismic wave propagates through the target reservoir; the first attribute information of the location point is how the reflection coefficient of the seismic wave changes with the incident angle of the seismic wave at the location point; the first attribute information includes an intercept attribute and a gradient attribute; the target well log is a well within the target reservoir for which marl identification is required; and the location point is a point within the target well log;

[0011] a second attribute information determining module, configured to determine second attribute information of a plurality of location points based on the first attribute information of the plurality of location points, wherein the second attribute information of the location points is attribute information for distinguishing the top and bottom interfaces of the marl, constructed based on differences in the first attribute information caused by the marl interlayer at the location points;

[0012] a rock state determination module, configured to determine rock states corresponding to the plurality of position points based on the second attribute information of the plurality of position points, wherein the rock states indicate whether the position points are top and bottom interfaces of marl;

[0013] The marl determination module is used to determine whether the target well contains marl according to the rock states corresponding to the plurality of location points.

[0014] According to another aspect of the present invention, an electronic device is provided, comprising:

[0015] at least one processor; and

[0016] a memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor so that the at least one processor can perform the marl identification method according to any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the marl identification method according to any embodiment of the present invention when executed.

[0019] The technical solution of the embodiment of the present invention determines the first attribute information of several location points in the target well logging; determines the second attribute information of the several location points based on the first attribute information, and can characterize the lithologic sensitivity characteristics contained in the inversion data through the second attribute parameters, providing a basis for the subsequent determination of marl; determines the rock state corresponding to the several location points based on the second attribute information of the several location points, and can ensure the accuracy of the rock state determination; and determines whether the target well logging contains marl based on the rock state corresponding to the several location points. This method determines the rock state of the location points through the second attribute information, and determines whether marl is present in the target well logging based on the rock state. The introduction of the second attribute information can fully consider the sensitive parameters caused by different lithologies within the rock, thereby improving the accuracy of marl identification.

[0020] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 A flow chart of a marl identification method provided by an embodiment of the present invention;

[0023] Figure 2 A schematic diagram of target synthetic seismic data provided by an embodiment of the present invention;

[0024] Figure 3 A schematic diagram of second attribute information of different target well logging provided by an embodiment of the present invention;

[0025] Figure 4 A schematic diagram of marl in a target reservoir provided by an embodiment of the present invention;

[0026] Figure 5 A schematic diagram of the change of an incident angle over time provided by an embodiment of the present invention;

[0027] Figure 6 A schematic diagram of changes in the incident angle and the first attribute information over time at different depths of target synthetic seismic data provided by an embodiment of the present invention;

[0028] Figure 7 A schematic structural diagram of a marl identification device provided by an embodiment of the present invention;

[0029] Figure 8 A schematic structural diagram of an electronic device for implementing the marl identification method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0032] Figure 1 This is a flow chart of a marl identification method provided by an embodiment of the present invention. This embodiment is applicable to obtaining the distribution of marl in a reservoir. The method can be executed by a marl identification device. The marl identification device can be implemented in the form of hardware and / or software. The marl identification device can be configured in any electronic device with network communication function. Figure 1 As shown, the method includes:

[0033] S110: Determine first attribute information of a plurality of location points in the target well logging.

[0034] The first attribute information is used to characterize how the reflection coefficient of the seismic wave changes with the incident angle of the seismic wave when the seismic wave propagates in the target reservoir.

[0035] The first attribute information of the location point is the change of the reflection coefficient of the seismic wave at the location point with the incident angle of the seismic wave.

[0036] The first attribute information includes an intercept attribute and a gradient attribute.

[0037] Further, the intercept attribute represents the P-wave reflection coefficient when the seismic wave is vertically incident, which is related to the wave impedance difference of the upper and lower media of the rock layer; the gradient attribute is used to reflect the rate of change of the reflection coefficient with the incident angle or offset.

[0038] The target well is a well in a target reservoir in which the mudstone needs to be identified.

[0039] Specifically, the logging data is preprocessed, forward simulation is performed, a preset relationship is established according to the simulated data, and the preset relationship is solved to obtain first attribute information of a plurality of position points in the target well.

[0040] The preset relationship is a relationship between the reflection angle and the reflection coefficient established according to the P-wave velocity, the density and the Poisson's ratio of the plurality of position points in the target well.

[0041] Further, the parameter term in the preset relationship can represent the intercept attribute and the gradient attribute.

[0042] As shown in FIG. 1, the black line is the logging data, and the red line is the data after the coarsening and the forward simulation. Figure 2 As shown in FIG. 1, the black line is the logging data, and the red line is the data after the coarsening and the forward simulation.

[0043] S120, according to the first attribute information of the plurality of position points, determining second attribute information of the plurality of position points.

[0044] The second attribute information of the position point is attribute information used to distinguish the top and bottom boundaries of the mudstone interlayer, which is constructed according to the difference in the first attribute information caused by the mudstone interlayer at the position point.

[0045] Specifically, the second attribute information of the plurality of position points is determined according to the positive and negative of the first attribute information of the plurality of position points.

[0046] Further, if the intercept attribute of the position point is negative and the gradient attribute is positive, the second attribute information of the position point is the absolute value of the product of the intercept attribute and the gradient attribute; if the intercept attribute of the position point is positive and the gradient attribute is negative, the second attribute information of the position point is the negative of the absolute value of the product of the intercept attribute and the gradient attribute; if the intercept attribute of the position point is negative and the gradient attribute is negative or the intercept attribute is positive and the gradient attribute is positive, the second attribute information of the position point is 0.

[0047] As shown in FIG. 1, the black line is the logging data, and the red line is the data after the coarsening and the forward simulation. Figure 3 As shown in FIG. 1, the black line is the logging data, and the red line is the data after the coarsening and the forward simulation. 9 -1.9×109 The second attribute information of the two position points in the target well numbered C is 0.3×10 9 Left and right and -2.2×10 9 The second attribute information of the two position points in the target well numbered D is 1.8×10 9 Left and right -2×10 9 The second attribute information of the two position points in the target well numbered E is 1.0×10 9 Left and right -1.7×10 9 about.

[0048] S130: Determine rock states corresponding to the plurality of location points based on the second attribute information of the plurality of location points.

[0049] Among them, the rock state is characterized by whether the location point is the top and bottom interface of the marl.

[0050] Specifically, if the second attribute information of the location point is greater than the first preset threshold, the second attribute information of the location point is represented as a positive attribute, and the location point is the top interface of marl; if the second attribute information of the location point is less than the second preset threshold, the second attribute information of the location point is represented as a negative attribute, and the location point is the bottom interface of marl; if the second attribute information of the location point is within the interval formed by the first preset threshold and the second preset threshold, the location point is a non-marl interface.

[0051] For example, Figure 3 As shown, the two positions in the target logging well numbered A are both non-marl interfaces; the two positions in the target logging well numbered B are one marl top interface and one non-marl interface; the two positions in the target logging well numbered C are both non-marl; the two positions in the target logging well numbered D are one marl top interface and one non-marl interface; the two positions in the target logging well numbered E are both non-marl interfaces.

[0052] S140: Determine whether the target logging well contains marl based on rock conditions corresponding to a plurality of location points.

[0053] Specifically, if there is at least one position point with a rock state of the top interface of marl and at least one position point with a rock state of the bottom interface of marl in the target well logging, then the target well logging contains marl; if there is only a position point with a rock state of the top interface of marl or only contains a position point with a rock state of the bottom interface of marl, then the target well logging does not contain marl; if the rock state of the position points in the target well logging are all non-marl interfaces, then the target well logging does not contain marl.

[0054] For example, Figure 4As shown, the target logging well numbered A contains multiple marls, as indicated by the black arrows; the target logging well numbered B also contains multiple marls.

[0055] Optionally, determining first attribute information of a plurality of location points in a target well logging includes steps A1-A2:

[0056] Step A1: Determine target synthetic seismic data.

[0057] The target synthetic seismic data is the well logging data after scale coarsening and forward simulation, and the well logging data is data that can represent the geological information of the target well logging.

[0058] Specifically, after the well logging data is scaled and forward modeled, it is compared with the wellside gather data to obtain the target synthetic seismic data.

[0059] Step A2: determining first attribute information of a plurality of location points in the target well according to the target synthetic seismic data.

[0060] Specifically, a preset relationship is established based on the target synthetic seismic data, and the preset relationship is solved to obtain first attribute information of a plurality of position points in the target logging well.

[0061] The preset relationship is established based on target synthetic seismic data to characterize the relationship between the reflection coefficient and the reflection angle.

[0062] For example, the preset relationship can be expressed by the following formula:

[0063]

[0064] Among them, R pp (θ) is the reflection coefficient; θ is the reflection angle; ΔV p is the difference in longitudinal wave velocity between the upper and lower media at the location point; is the average value of the longitudinal wave velocity of the media above and below the position point; A0 is a parameter; Δσ is the difference in Poisson's ratio terms; is the average value of Poisson’s ratio. s .

[0065] Where, ΔV p It can be expressed by the following formula:

[0066] ΔV P =V P2 -V P1 ,

[0067] Among them, V p1 is the longitudinal wave velocity of the medium at the position point; V p2 is the longitudinal wave velocity of the medium at the position point.

[0068] Furthermore, It can be expressed by the following formula:

[0069]

[0070] Furthermore, Δσ can be expressed by the following formula:

[0071] Δσ=σ2-σ1,

[0072] Among them, σ1 is the Poisson's ratio term of the medium at the position point; σ2 is the Poisson's ratio term of the medium below the position point.

[0073] Furthermore, It can be expressed by the following formula:

[0074]

[0075] Furthermore, A0 can be expressed by the following formula:

[0076]

[0077] Wherein, B can be represented by the following formula:

[0078]

[0079] Where Δρ is the difference in density between the upper and lower media at the location point; is the average density of the medium above and below the position point; ΔV p is the difference in longitudinal wave velocity between the upper and lower media at the location point; is the average longitudinal wave velocity of the media above and below the location point.

[0080] Among them, Δρ can be expressed by the following formula:

[0081] Δρ=ρ2-ρ1,

[0082] Among them, ρ1 is the density of the medium at the position point; ρ2 is the density of the medium below the position point.

[0083] Furthermore, It can be expressed by the following formula:

[0084]

[0085] Furthermore, let P = R0, Then the default relationship can be written as:

[0086]

[0087] Among them, P is the intercept attribute; G is the gradient attribute.

[0088] Furthermore, when the incident angle is less than 30°, the influence of the third term on the reflection coefficient can be ignored, and the preset relationship can be simplified to:

[0089] R pp (θ)=P+Gsin 2 θ.

[0090] Furthermore, taking the incident angle of 30° as an example, the relationship between the intercept attribute and gradient attribute at different positions and the incident angle and reflection coefficient can be obtained according to the above formula:

[0091]

[0092] Furthermore, the above equation is solved by the least squares method to obtain the intercept attribute and gradient attribute of different position points.

[0093] For example, Figure 5 As shown in FIG, the change of different incident angles with time. It can be seen from the figure that the change of the incident angle is the largest within 10-20ms.

[0094] For example, Figure 6 As shown in the figure, the incident angle, intercept attribute, and gradient attribute corresponding to the P-wave velocity, S-wave velocity, and density at the location point can be seen. As marked by the red line in the figure, both the gradient attribute and the intercept attribute have extreme points.

[0095] Optionally, determining target synthetic seismic data includes steps B1-B3:

[0096] Step B1: determine the target well logging data and perform scale coarsening on the well logging data to obtain data to be processed.

[0097] Specifically, the logging data of the target well is acquired from the target reservoir by means of the logging equipment, and the logging data is coarsened to obtain the data to be processed.

[0098] Step B2: Perform forward modeling on the data to be processed to obtain reference synthetic seismic data.

[0099] Specifically, forward modeling is performed on the data to be processed using a forward modeling method to obtain reference synthetic seismic data.

[0100] For example, Figure 2 As shown, the black line is the well logging data; the red line is the reference synthetic seismic data. It can be seen from the figure that the change frequency of the red line is lower than that of the black line.

[0101] Furthermore, the coarsening process in the above step is due to the high frequency of logging data acquisition, which causes the data to fluctuate drastically and does not match the seismic scale. Therefore, coarsening is necessary to ensure that the scale matches. After coarsening, the changing trends of the seismic data can be more intuitively observed.

[0102] Step B3: perform data feature matching between the reference synthetic seismic data and the wellbore side seismic data at depth. If the features are consistent, the reference synthetic seismic data is used as the target synthetic seismic data.

[0103] Specifically, the reflection characteristics and simulation results of the reference synthetic seismic data and the wellbore seismic data of the actual target logging are compared at depth. If the comparison results are consistent, the reference synthetic seismic data is used as the target synthetic seismic data; if the matching results are inconsistent, the data is reprocessed.

[0104] The above steps, which correspond to the seismic data beside the wellbore, are to prevent the changes in the rock formation represented by the forward simulation data from not matching the actual rock formation changes in the target well logging, thereby causing deviations in the identification of marl.

[0105] Optionally, determining second attribute information of a plurality of location points based on the first attribute information includes steps C1-C3:

[0106] Step C1: If the intercept attribute is less than zero and the gradient attribute is greater than zero, the second attribute information is the absolute value of the product of the intercept attribute and the gradient attribute.

[0107] For example, if P<0 and G>0, then F=|P*G|.

[0108] Step C2: If the intercept attribute is greater than zero and the gradient attribute is less than zero, the second attribute information is the negative value of the absolute value of the product of the intercept attribute and the gradient attribute.

[0109] For example, if P>0 and G<0, then F=-|P*G|.

[0110] Step C3: If the intercept attribute is less than zero and the gradient attribute is less than zero or the intercept attribute is greater than zero and the gradient attribute is greater than zero, the second attribute information is zero.

[0111] For example, if P≤0 and G≤0 or P>0 and G>0, then F=0.

[0112] For example, the second attribute information of different location points can be expressed by the following formula:

[0113]

[0114] Among them, P is the intercept attribute; G is the gradient attribute.

[0115] Optionally, determining the rock states corresponding to the plurality of location points based on the second attribute information of the plurality of location points includes steps D1-D3:

[0116] Step D1: If the second attribute information of the location point is greater than a first preset threshold, the rock state of the location point is the top interface of marl.

[0117] For example, if the second attribute information F of the location point is greater than 1.0198*10 8 When , it belongs to the positive anomaly of F attribute, that is, the rock state of the location point is the top interface of marl.

[0118] Step D2: If the second attribute information of the location point is less than a second preset threshold, the rock state of the location point is the bottom interface of marl.

[0119] For example, if the second attribute information F of the location point is less than -4.4074*10 8 When , it belongs to the negative anomaly of F attribute, that is, the rock state of the location point is the bottom interface of marl.

[0120] Step D3: If the second attribute information of the location point is less than the first preset threshold and greater than the second preset threshold, the rock state of the location point is a non-marlstone interface.

[0121] For example, -4.4074*10 8 <The second attribute information of the location point F<1.0198*10 8 , then the rock state at the location point is considered to be a non-marlstone interface.

[0122] Optionally, determining whether the target well contains marl according to the rock conditions corresponding to a plurality of location points includes steps E1-E2:

[0123] Step E1: If, among the rock states corresponding to the plurality of position points, one has a rock state of a marl top interface and the other has a rock state of a marl bottom interface, then the target logging well contains marl.

[0124] Specifically, if at least one marl top interface and at least one marl bottom interface simultaneously exist in the rock states corresponding to several position points, it is considered that the target logging well contains marl.

[0125] Step E2: If among the rock states corresponding to the plurality of position points, only one rock state is the top interface of marl, or only one rock state is the bottom interface of marl, then the target logging well does not contain marl.

[0126] Specifically, if the rock states corresponding to several position points only include the top interface of marl but not the bottom interface of marl; or only include the bottom interface of marl but not the top interface of marl, it is considered that the target logging well does not contain marl.

[0127] Further, if the rock states of the plurality of position points are all non-mudstone interfaces, it is directly considered that the target well does not contain mudstone.

[0128] The technical scheme of the embodiment determines first attribute information of a plurality of position points in a target well, determines second attribute information of the plurality of position points according to the first attribute information, can represent the lithology sensitivity characteristics contained in the inversion data through the second attribute parameters, provides a basis for subsequent mudstone judgment, judges the rock states of the plurality of position points according to the second attribute information of the plurality of position points, can ensure the accuracy of the rock state determination, and determines whether the target well contains mudstone according to the rock states of the plurality of position points. The method judges the rock states of the position points through the second attribute information, judges whether the target well contains mudstone according to the rock states, the introduction of the second attribute information can fully consider the sensitive parameters caused by different lithologies in the rock, and thus the accuracy of mudstone identification is improved.

[0129] Figure 7 A structural schematic diagram of a mudstone identification device provided by the embodiment is shown. The embodiment can be applied to obtain the distribution of mudstone in a reservoir, the mudstone identification device can be realized in the form of hardware and / or software, and the mudstone identification device can be configured in any electronic device with network communication function. As shown in the figure, the device includes a first attribute information determination module 210, a second attribute information determination module 220, a rock state determination module 230, and a mudstone determination module 240, wherein: Figure 7

[0130] The first attribute information determination module 210 is configured to determine first attribute information of a plurality of position points in a target well, the first attribute information is used to represent the change of the reflection coefficient of a seismic wave with the incidence angle of the seismic wave when the seismic wave propagates in a target reservoir, the first attribute information of a position point is the change of the reflection coefficient of a seismic wave with the incidence angle of the seismic wave at the position point, the first attribute information includes an intercept attribute and a gradient attribute, the target well is a well in the target reservoir that needs to be identified for mudstone, and the position point is a point in the target well;

[0131] The second attribute information determination module 220 is configured to determine second attribute information of the plurality of position points according to the first attribute information of the plurality of position points, and the second attribute information of the position point is attribute information for distinguishing the top and bottom interfaces of mudstone, which is constructed according to the difference of the first attribute information caused by the mudstone interlayer at the position point;

[0132] The rock state determination module 230 is configured to judge the rock states of the plurality of position points according to the second attribute information of the plurality of position points, and the rock state represents whether the position point is the top and bottom interfaces of mudstone; ​

[0133] The marl determination module 240 is used to determine whether the target well contains marl according to the rock conditions corresponding to a number of location points.

[0134] Optionally, the first attribute information determining module 210 includes:

[0135] Target synthetic seismic data determination unit: used to determine target synthetic seismic data, the target synthetic seismic data is the well logging data after scale coarsening and forward simulation, and the well logging data is data that can represent the geological information of the target well logging;

[0136] The first attribute information determining unit is used to determine the first attribute information of a plurality of position points in the target well according to the target synthetic seismic data.

[0137] Optionally, the target synthetic seismic data determination unit includes:

[0138] The unit for determining data to be processed is used to determine the logging data of the target well and perform scale coarsening on the logging data to obtain the data to be processed;

[0139] Reference synthetic seismic data determination unit: used for performing forward modeling on the data to be processed to obtain reference synthetic seismic data;

[0140] Target synthetic seismic data determination unit: used to match the data features of the reference synthetic seismic data with the wellbore seismic data at depth. If the features are consistent, the reference synthetic seismic data is used as the target synthetic seismic data.

[0141] Optionally, the second attribute information determining module 220 is specifically configured to:

[0142] If the intercept attribute is less than zero and the gradient attribute is greater than zero, the second attribute information is the absolute value of the product of the intercept attribute and the gradient attribute;

[0143] If the intercept attribute is greater than zero and the gradient attribute is less than zero, the second attribute information is the negative value of the absolute value of the product of the intercept attribute and the gradient attribute;

[0144] If the intercept attribute is less than zero and the gradient attribute is less than zero, or if the intercept attribute is greater than zero and the gradient attribute is greater than zero, the second attribute information is zero.

[0145] Optionally, the rock state determination module 230 includes:

[0146] A marl top interface determination unit is configured to determine that the rock state of the location point is the marl top interface if the second attribute information of the location point is greater than a first preset threshold value;

[0147] A marl bottom interface determination unit is configured to determine that the rock state of the location point is the marl bottom interface if the second attribute information of the location point is less than a second preset threshold value;

[0148] Non-marl interface determination unit: used for determining that the rock state of the location point is a non-marl interface if the second attribute information of the location point is less than a first preset threshold and greater than a second preset threshold.

[0149] Optionally, the marl determination module 240 is specifically configured to:

[0150] If among the rock states corresponding to several locations, one has a marl top interface and the other has a marl bottom interface, then the target well contains marl.

[0151] If among the rock states corresponding to several position points, only the rock state is the top interface of marl, or only the rock state is the bottom interface of marl, then the target logging well does not contain marl.

[0152] The marl identification device provided in the embodiment of the present invention can execute the marl identification method provided in any embodiment of the present invention described above, and has the corresponding functions and beneficial effects of executing the marl identification method. For detailed processes, please refer to the relevant operations of the marl identification method in the aforementioned embodiment.

[0153] Figure 8 A schematic diagram of the structure of an electronic device for implementing the marl identification method according to an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0154] like Figure 8As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0155] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0156] The processor 11 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any other suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the marl identification method.

[0157] In some embodiments, the marl identification method can be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the marl identification method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to execute the marl identification method in any other suitable manner (e.g., via firmware).

[0158] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system comprising at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0159] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0160] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0161] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0162] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0163] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0164] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0165] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A marl identification method, characterized in that: include: Determining first attribute information for a plurality of location points in a target well log, the first attribute information being used to characterize how a reflection coefficient of a seismic wave changes with the incident angle of the seismic wave as the seismic wave propagates in a target reservoir; the first attribute information for each location point being how the reflection coefficient of the seismic wave changes with the incident angle of the seismic wave at that location point; the first attribute information comprising an intercept attribute and a gradient attribute; the target well log being a well in the target reservoir for which marl identification is required; and the location point being a point in the target well log; Determining second attribute information of a plurality of location points based on the first attribute information of the plurality of location points, wherein the second attribute information of the location points is attribute information for distinguishing the top and bottom interfaces of the marl, constructed based on differences in the first attribute information caused by the marl interlayer at the location points; Determining rock states corresponding to the plurality of position points based on the second attribute information of the plurality of position points, wherein the rock states indicate whether the position points are top and bottom interfaces of marl; Determine whether the target well contains marl according to the rock states corresponding to the plurality of location points.

2. The method according to claim 1, characterized in that The determining of first attribute information of a plurality of location points in the target well logging includes: Determining target synthetic seismic data, wherein the target synthetic seismic data is well logging data after scale coarsening and forward modeling, and the well logging data is data that can represent geological information of the target well logging; First attribute information of a plurality of location points in the target well logging is determined based on the target synthetic seismic data.

3. The method according to claim 2, characterized in that The determining of target synthetic seismic data includes: Determining the well logging data of the target well logging, and performing scale coarsening on the well logging data to obtain data to be processed; Performing forward simulation on the data to be processed to obtain reference synthetic seismic data; The reference synthetic seismic data and the wellbore side seismic data are matched in terms of data features at depth. If the features are consistent, the reference synthetic seismic data is used as the target synthetic seismic data.

4. The method according to claim 1, wherein The determining the second attribute information of the plurality of location points based on the first attribute information of the plurality of location points includes: If the intercept attribute is less than zero and the gradient attribute is greater than zero, the second attribute information is the absolute value of the product of the intercept attribute and the gradient attribute; If the intercept attribute is greater than zero and the gradient attribute is less than zero, the second attribute information is the negative value of the absolute value of the product of the intercept attribute and the gradient attribute; If the intercept attribute is less than zero and the gradient attribute is less than zero, or if the intercept attribute is greater than zero and the gradient attribute is greater than zero, the second attribute information is zero.

5. The method according to claim 1, wherein The determining of rock states corresponding to the plurality of location points based on the second attribute information of the plurality of location points includes: If the second attribute information of the location point is greater than the first preset threshold, the rock state of the location point is the top interface of marl; If the second attribute information of the location point is less than a second preset threshold, the rock state of the location point is the bottom interface of marl; If the second attribute information of the location point is less than the first preset threshold and greater than the second preset threshold, the rock state of the location point is a non-marlstone interface.

6. The method according to claim 1, characterized in that The determining whether the target well contains marl according to the rock states corresponding to the plurality of location points includes: If one of the rock states corresponding to the plurality of position points is a marl top interface and the other is a marl bottom interface, then the target well contains marl; If, among the rock states corresponding to the plurality of position points, only one rock state is the top interface of marl, or only one rock state is the bottom interface of marl, then the target well logging does not contain marl.

7. A marl identification device, characterized in that: include: A first attribute information determination module is configured to determine first attribute information of a plurality of location points within a target well log, wherein the first attribute information is configured to characterize how the reflection coefficient of a seismic wave changes with the incident angle of the seismic wave as the seismic wave propagates through the target reservoir; the first attribute information of the location point is how the reflection coefficient of the seismic wave changes with the incident angle of the seismic wave at the location point; the first attribute information includes an intercept attribute and a gradient attribute; the target well log is a well within the target reservoir for which marl identification is required; and the location point is a point within the target well log; a second attribute information determining module, configured to determine second attribute information of a plurality of location points based on the first attribute information of the plurality of location points, wherein the second attribute information of the location points is attribute information for distinguishing the top and bottom interfaces of the marl, constructed based on differences in the first attribute information caused by the marl interlayer at the location points; a rock state determination module, configured to determine rock states corresponding to the plurality of position points based on the second attribute information of the plurality of position points, wherein the rock states indicate whether the position points are top and bottom interfaces of marl; The marl determination module is used to determine whether the target well contains marl according to the rock states corresponding to the plurality of location points.

8. The device according to claim 7, characterized in that The rock state determination module includes: a marl top interface determination unit, configured to determine that the rock state of the location point is the top interface of marl if the second attribute information of the location point is greater than a first preset threshold; a marl bottom interface determination unit, configured to determine that the rock state of the location point is the marl bottom interface if the second attribute information of the location point is less than a second preset threshold; A non-marl interface determining unit is configured to determine that, if the second attribute information of the location point is less than a first preset threshold value and greater than a second preset threshold value, the rock state of the location point is a non-marl interface.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor to enable the at least one processor to perform the marl identification method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the marl identification method according to any one of claims 1 to 7 when executed.

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