Marlstone identification method and device, electronic equipment and storage medium

Abstract

The invention discloses a marlstone 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 logging well; 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 logging contains marlstone or not according to the rock states corresponding to the plurality of position points. According to the method, the rock state of the position point is judged through the second attribute information, whether marlstone exists in the target logging or not is judged according to the rock state, sensitive parameters caused by different lithology in the rock can be fully considered due to introduction of the second attribute information, and therefore the marlstone recognition precision is improved.

Description

Technical Field

[0001] The present invention relates to the field of geological prospecting 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 marls 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 accurately identify marls. However, the existing technology usually obtains the corresponding lithology sensitive parameters through rock physics analysis of lithology identification by inversion of seismic data, thereby completing 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 lithology sensitive parameters through rock physics analysis, and it is impossible to use lithology sensitive parameters to distinguish different lithologies, which makes it 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] Determine the first attribute information of a plurality of position points in the target well logging, wherein the first attribute information is used to characterize the change of the reflection coefficient of the seismic wave with the incident angle of the seismic wave when the seismic wave propagates in the target reservoir; the first attribute information of the position point is the change of the reflection coefficient of the seismic wave with the incident angle of the seismic wave at the position point; the first attribute information includes an intercept attribute and a gradient attribute; the target well logging is a well in the target reservoir that needs to be identified as marl; the position point is a point in the target well logging;

[0006] Determining second attribute information of a plurality of position points according to the first attribute information of the plurality of position points, wherein the second attribute information of the position points is attribute information for distinguishing the top and bottom interfaces of the marlstone and is constructed according to the difference of the first attribute information caused by the marlstone interlayer at the position points;

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

[0008] Whether the target well logging contains marl is determined according to the rock states corresponding to the plurality of position points.

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

[0010] A first attribute information determination module is used to determine first attribute information of a plurality of position points in a target well logging, wherein the first attribute information is used to characterize the change of the reflection coefficient of the seismic wave with the incident angle of the seismic wave when the seismic wave propagates in the target reservoir; the first attribute information of the position point is the change of the reflection coefficient of the seismic wave with the incident angle of the seismic wave at the position point; the first attribute information includes an intercept attribute and a gradient attribute; the target well logging is a well in the target reservoir that needs to be identified as marl; and the position point is a point in the target well logging;

[0011] A second attribute information determination module, used to determine second attribute information of a plurality of position points according to the first attribute information of the plurality of position points, wherein the second attribute information of the position points is attribute information for distinguishing the top and bottom interfaces of the marlstone constructed according to the difference of the first attribute information caused by the marlstone interlayer at the position points;

[0012] A rock state determination module, used for determining the rock state corresponding to the plurality of position points according to the second attribute information of the plurality of position points, wherein the rock state indicates whether the position points are the top and bottom interfaces of the marlstone;

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

[0014] According to another aspect of the present invention, an electronic device is provided, the electronic device 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, and the computer program is executed by the at least one processor so that the at least one processor can execute the marl identification method described in 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 described in 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 position points in the target well logging; determines the second attribute information of several position points based on the first attribute information, and can characterize the lithology 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 several position points based on the second attribute information of several position points, and can ensure the accuracy of the rock state determination; determines whether the target well logging contains marl based on the rock state corresponding to several position points. This method determines the rock state of the position points through the second attribute information, and determines whether marl exists 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 in the rock, thereby improving the accuracy of marl identification.

[0020] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily 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 a 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 the change of 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 diagram of the structure of a marl identification device provided by an embodiment of the present invention;

[0029] 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. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme 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 described embodiments 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 creative work should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first", "second", etc. in the specification 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 data 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 that are 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 can be applied to obtain 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, determining first attribute information of a plurality of location points in the target well logging.

[0034] The first attribute information is used to characterize the change of the reflection coefficient of the seismic wave 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] Furthermore, the intercept attribute characterizes the longitudinal wave reflection coefficient when the seismic wave is incident vertically, which is related to the wave impedance difference between the upper and lower media of the rock layer; the gradient attribute is used for the rate of change of the reflection coefficient with the incident angle or offset distance.

[0038] The target well logging is the well in the target reservoir that needs to be identified for marl. The location point is the point in the target well logging.

[0039] Specifically, the logging data is preprocessed and forward modeled, a preset relationship is established based on the simulated data, the preset relationship is solved, and the first attribute information of a plurality of position points in the target logging is obtained.

[0040] The preset relationship is established based on the longitudinal wave velocity, density and Poisson's ratio of several position points in the target logging, and is used to characterize the relationship between the reflection angle and the reflection coefficient.

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

[0042] For example, Figure 2 As shown, the black line is the logging data; the red line is the data after coarsening and forward simulation. It can be seen from the figure that the change frequency of the red line is lower than that of the black line.

[0043] S120. Determine second attribute information of the plurality of location points according to the first attribute information of the plurality of location points.

[0044] The second attribute information of the position point is attribute information for distinguishing the top and bottom interfaces of the marlstone constructed according to the difference in the first attribute information caused by the marlstone interlayer at the position point.

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

[0046] Furthermore, 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] For example, Figure 3 As shown in the figure, it can be seen that the second attribute information of the two position points in the target well numbered A, that is, the absolute value of the F attribute in the figure does not exceed 1; the second attribute information of the two position points in the target well numbered B is 3×10 9 Left and right -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 -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 according to 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 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 characterized 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 characterized 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 numbered A are both non-marl interfaces; the two positions in the target logging numbered B are one marl top interface and one non-marl interface; the two positions in the target logging numbered C are both non-marl; the two positions in the target logging numbered D are one marl top interface and one non-marl interface; the two positions in the target logging numbered E are both non-marl interfaces.

[0052] S140: Determine whether the target logging well contains marl according to the rock states corresponding to the plurality of position 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, 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, the target well logging does not contain marl; if the rock states of the positions in the target well logging are all non-marl interfaces, 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 positions marked by 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 the 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 modeling, and the well logging data is data that can characterize 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 logging according to the target synthetic seismic data.

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

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

[0062] Exemplarily, 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 media above and below the position 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; is the average value of the Poisson’s ratio term. Where σ is used to replace the shear wave velocity V 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 V is the longitudinal wave velocity of the medium at the position point; p2 is the longitudinal wave velocity of the medium at the position point.

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

[0074]

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

[0076]

[0077] Among them, B can be expressed by the following formula:

[0078]

[0079] Among them, Δρ is the difference in density between the upper and lower media at the position 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 media above and below the position point; is the average value of the longitudinal wave velocity of the medium 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] Further, It can be expressed by the following formula:

[0084]

[0085] Further, let P = R0, 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 square method to obtain the intercept attribute and gradient attribute of different position points.

[0093] For example, Figure 5 As shown, the changes 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, it can be seen that the incident angle, intercept attribute and gradient attribute corresponding to the longitudinal wave velocity, shear wave velocity and density of the position point. As shown in the red line position in the figure, there are extreme points in the gradient attribute and intercept attribute.

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

[0096] Step B1: determine the well logging data of the target well logging, and scale the well logging data to obtain data to be processed.

[0097] Specifically, the well logging data of the target well logging is acquired from the target reservoir by means of the well logging equipment, and the well 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, the data to be processed are forward simulated by a forward modeling method to obtain reference synthetic seismic data.

[0100] For example, Figure 2 As shown, the black line is the 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 above steps are performed for coarsening because the frequency of logging data acquisition is too high, resulting in drastic changes in the data and mismatching with the seismic scale. Therefore, coarsening is required to ensure matching in scale, and after data coarsening, the changing trend of seismic data can be observed more intuitively.

[0102] Step B3: Match the data features of 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 correspond to the seismic data beside the wellbore to prevent the change of the rock formation represented by the data after forward simulation from not matching the actual rock formation change of the target well logging, thereby causing deviation in the identification of marl.

[0105] Optionally, determining second attribute information of a plurality of location points according to 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] Exemplarily, 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] Exemplarily, 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] Exemplarily, if P≤0 and G≤0 or P>0 and G>0, then F=0.

[0112] Exemplarily, the second attribute information of different position points can be expressed by the following formula:

[0113]

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

[0115] Optionally, judging the rock states corresponding to the plurality of position points according to the second attribute information of the plurality of position points includes steps D1-D3:

[0116] Step D1: 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.

[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 F attribute positive anomaly, 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 the 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 value and greater than the second preset threshold value, 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 logging contains marl according to the rock states corresponding to a plurality of position points includes steps E1-E2:

[0123] Step E1: If among the rock states corresponding to the plurality of position points, one rock state is a marl top interface and the other rock state is 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 a plurality of 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 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.

[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 include marl.

[0127] Furthermore, if the rock states at several locations are all non-marl interfaces, it is directly considered that the target well logging does not contain marl.

[0128] The technical solution of this embodiment determines the first attribute information of several position points in the target well logging; determines the second attribute information of several position points based on the first attribute information, and can characterize the lithology sensitivity contained in the inversion data through the second attribute parameter, providing a basis for the subsequent determination of marl; determines the rock state corresponding to several position points based on the second attribute information of several position points, and can ensure the accuracy of the rock state determination; determines whether the target well logging contains marl based on the rock state corresponding to several position points. This method determines the rock state of the position points through the second attribute information, and determines whether marl exists 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 in the rock, thereby improving the accuracy of marl identification.

[0129] Figure 7 The structure diagram of a marl identification device provided by an embodiment of the present invention is shown in FIG. This embodiment can be applied to obtain the distribution of marl in a reservoir. 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 7 As shown, 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 marl determination module 240, wherein:

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

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

[0132] The rock state determination module 230 is used to determine the rock state corresponding to the plurality of position points according to the second attribute information of the plurality of position points, wherein the rock state indicates whether the position point is the top and bottom interface of the marlstone;

[0133] The marl determination module 240 is used to determine whether the target well contains marl according to the rock states 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 the data that can characterize 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 logging according to the target synthetic seismic data.

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

[0138] The unit for determining data to be processed is used to determine the well logging data of the target well logging, and to scale the well 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 side 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 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: used for determining 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: used for determining 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-marlstone interface determination unit: used to determine that the rock state of the location point is a non-marlstone interface 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.

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

[0150] If among the rock states corresponding to several position points, 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 mentioned above, and has the corresponding functions and beneficial effects of executing the marl identification method. For detailed process, please refer to the relevant operations of the marl identification method in the above embodiment.

[0153] Figure 8 A schematic diagram of the structure of an electronic device for implementing the marl identification method of an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, 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 required herein.

[0154] like Figure 8As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and 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 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0155] A number of 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 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 through a computer network such as the Internet and / or various telecommunication networks.

[0156] The processor 11 may be a variety of general and / or special processing components 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 special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate 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 may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the marl identification method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the marl identification method in any other appropriate manner (e.g., by means of firmware).

[0158] Various implementations of the systems and techniques described above 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), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including 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, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

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

[0161] To provide interaction with a user, the systems and techniques described herein may 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 a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0162] The systems and techniques described herein may be implemented in a computing system that includes backend 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 frontend components (e.g., a user computer with a graphical user interface or a 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 backend components, middleware components, or frontend components. The components of the system may 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 a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0164] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0165] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for identifying marl, characterized in that: include: Determine the first attribute information of a plurality of position points in the target well logging, wherein the first attribute information is used to characterize the change of the reflection coefficient of the seismic wave with the incident angle of the seismic wave when the seismic wave propagates in the target reservoir; the first attribute information of the position point is the change of the reflection coefficient of the seismic wave with the incident angle of the seismic wave at the position point; the first attribute information includes an intercept attribute and a gradient attribute; the target well logging is a well in the target reservoir that needs to be identified as marl; the position point is a point in the target well logging; Determining second attribute information of a plurality of position points according to the first attribute information of the plurality of position points, wherein the second attribute information of the position points is attribute information for distinguishing the top and bottom interfaces of the marlstone and is constructed according to the difference of the first attribute information caused by the marlstone interlayer at the position points; Determining the rock states corresponding to the plurality of position points according to the second attribute information of the plurality of position points, wherein the rock states indicate whether the position points are the top and bottom interfaces of marlstone; Whether the target well logging contains marl is determined according to the rock states corresponding to the plurality of position points.

2. The method according to claim 1, characterized in that The step of determining first attribute information of a plurality of location points in the target well logging includes: Determine 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 capable of representing geological information of the target well logging; The first attribute information of a plurality of location points in the target well logging is determined according to the target synthetic seismic data.

3. The method according to claim 2, characterized in that The step of determining target synthetic seismic data comprises: Determine the well logging data of the target well logging, and perform scale coarsening on the well logging data to obtain data to be processed; Performing forward modeling 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, characterized in that The determining the second attribute information of the plurality of location points according to the first attribute information of the plurality of location points comprises: 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 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, characterized in that The step of determining the rock states corresponding to the plurality of position points according to the second attribute information of the plurality of position 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 logging contains marl according to the rock states corresponding to the plurality of position points comprises: 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 logging contains marl; If among the rock states corresponding to the plurality of 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 well logging does not contain marl.

7. A marl identification device, characterized in that: include: A first attribute information determination module is used to determine first attribute information of a plurality of position points in a target well logging, wherein the first attribute information is used to characterize the change of the reflection coefficient of the seismic wave with the incident angle of the seismic wave when the seismic wave propagates in the target reservoir; the first attribute information of the position point is the change of the reflection coefficient of the seismic wave with the incident angle of the seismic wave at the position point; the first attribute information includes an intercept attribute and a gradient attribute; the target well logging is a well in the target reservoir that needs to be identified as marl; and the position point is a point in the target well logging; A second attribute information determination module, used to determine second attribute information of a plurality of position points according to the first attribute information of the plurality of position points, wherein the second attribute information of the position points is attribute information for distinguishing the top and bottom interfaces of the marlstone constructed according to the difference of the first attribute information caused by the marlstone interlayer at the position points; A rock state determination module, used for determining the rock state corresponding to the plurality of position points according to the second attribute information of the plurality of position points, wherein the rock state indicates whether the position points are the top and bottom interfaces of the marlstone; The marl determination module is used to determine whether the target logging well contains marl according to the rock states corresponding to the plurality of position points.

8. The device according to claim 7, characterized in that The rock state determination module comprises: 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 value; 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 value; Non-marlstone interface determination unit: used for determining that the rock state of the location point is a non-marlstone interface 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.

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, and 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 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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