Stratum oil and gas reservoir identification method and device and computer equipment

Abstract

The invention discloses a stratum oil and gas reservoir identification method and device and computer equipment. The method comprises the following steps: acquiring logging data corresponding to a plurality of wells included in a target area, and target core data of a target well in the plurality of wells; according to the logging data corresponding to the multiple wells and the target core data, core granularity median values corresponding to the multiple wells are determined, and the core granularity median values corresponding to the multiple wells are used for describing rock properties of stratums of the corresponding wells; and according to the core granularity median values corresponding to the multiple wells, whether the target area has the stratum oil and gas reservoir or not is recognized. The reservoir forming identification method solves the technical problem that a reservoir forming identification method for a high-argillaceous sandstone reservoir is lacked in related technologies.

Description

Technical Field

[0001] The present invention relates to the technical field of reservoir formation identification, and in particular to a method, device and computer equipment for identifying stratum oil and gas reservoirs. Background Art

[0002] The core of oil and gas accumulation geology is the dynamic system and process of oil and gas migration and accumulation, which guides oil and gas exploration and subsequent potential development. The technology of predicting reservoir formation based on well logging data is an indispensable technology for oil fields at home and abroad. Its research runs through the entire process of oil fields from exploration and evaluation to development and depletion.

[0003] The interlayer heterogeneity of high-mud sandstone biogas reservoirs is serious, with vertical sand and mud intermixing. Due to the limitation of logging accuracy, the conventional logging data of high-mud sandstone biogas reservoirs show low resistivity and are difficult to distinguish gas content. Such layers generally have geological characteristics of high water saturation and low permeability. How to determine whether such reservoirs have effective accumulation from a geological perspective and have exploration and development value has always been a difficult problem in related technologies. At present, the analysis of gas content in high-mud reservoirs at home and abroad is mainly through seismic inversion to find favorable reservoirs, establish logging oil and water layer identification plates, and organic carbon content of source rocks. These methods are generally applied to shale gas reservoirs. The related technologies lack methods for predicting the accumulation of self-generated and self-storing high-mud sandstone reservoirs.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present invention provide a method, device and computer equipment for identifying oil and gas reservoirs in formations, so as to at least solve the technical problem that there is a lack of a method for identifying reservoirs of high-mud sandstone reservoirs in the related art.

[0006] According to one aspect of an embodiment of the present invention, a method for identifying stratigraphic oil and gas reservoirs is provided, comprising: obtaining well logging data corresponding to each of a plurality of wells included in a target area, and target core data of a target well among the plurality of wells; determining the median core grain sizes corresponding to each of the plurality of wells based on the well logging data corresponding to each of the plurality of wells, and the target core data, wherein the median core grain sizes corresponding to each of the plurality of wells are used to describe the rock properties of the formations of the corresponding wells; and identifying whether the target area has stratigraphic oil and gas reservoirs based on the median core grain sizes corresponding to each of the plurality of wells.

[0007] Optionally, according to the well logging data corresponding to the multiple wells respectively and the target core data, the median core grain sizes corresponding to the multiple wells are determined, including: determining the well logging data corresponding to the target well as the target well logging data among the well logging data corresponding to the multiple wells respectively; determining the median grain size function of the target area according to the target well logging data and the target core data, wherein the median grain size function describes the relationship between the well logging data corresponding to the multiple wells included in the target area and the median core grain sizes; bringing the well logging data corresponding to the multiple wells respectively into the median grain size function to determine the median core grain sizes corresponding to the multiple wells respectively.

[0008] Optionally, determining the median particle size function of the target area according to the target well logging data and the target core data includes: performing regression analysis on the target well logging data and the target core data to determine that the functional relationship between the target core data and the target well logging data is the median particle size function.

[0009] Optionally, before the logging data corresponding to the multiple wells are brought into the median grain size function to determine the median core grain sizes corresponding to the multiple wells, the method further includes: determining multiple differences between the logging data corresponding to the multiple wells and the target logging data; and performing standardization correction on the logging data corresponding to the multiple wells according to the multiple differences.

[0010] Optionally, it also includes: dividing the median core particle sizes corresponding to the multiple wells into multiple groups of data respectively located in different value intervals according to the values ​​of the median core particle sizes corresponding to the multiple wells; and setting different colors to visualize the multiple groups of data.

[0011] Optionally, based on the median core grain sizes corresponding to multiple wells, identifying whether the target area has stratigraphic oil and gas reservoirs includes: determining that the wells corresponding to the median core grain sizes that are less than the median grain size threshold are low-abundance wells, wherein the low-abundance wells are wells where the abundance of stratigraphic oil and gas reservoirs is lower than the exploitation threshold; the low-abundance wells are located without stratigraphic oil and gas reservoirs.

[0012] Optionally, it also includes: determining the mudstone layer thickness and formation thickness corresponding to the multiple wells respectively based on the logging data corresponding to the multiple wells respectively; determining the proportion of the mudstone layer thickness corresponding to the multiple wells respectively in the formation thickness based on the mudstone layer thickness and formation thickness corresponding to the multiple wells respectively; and determining that the wells corresponding to the proportion less than the mudstone layer proportion threshold are low-abundance wells.

[0013] Optionally, the method further includes: determining the reservoirs and cap layers corresponding to the multiple wells respectively based on the logging data corresponding to the multiple wells respectively; determining the difference between the gamma amplitude of the reservoirs and the gamma amplitude of the cap layers corresponding to the multiple wells respectively; and determining that the wells corresponding to the difference less than the gamma threshold are low-abundance wells.

[0014] Optionally, the method further includes: determining reservoir property parameters corresponding to the multiple wells respectively based on logging data corresponding to the multiple wells respectively, wherein the reservoir property parameters include at least one of the following: resistivity, acoustic wave time difference, mud content, gas saturation; and determining that the wells corresponding to the reservoir property parameters that are outside the range of the reservoir property parameters are low-abundance wells.

[0015] According to another aspect of an embodiment of the present invention, a stratigraphic oil and gas reservoir identification device is also provided, including: an acquisition module, used to acquire logging data corresponding to multiple wells included in the target area, and target core data of the target well among the multiple wells; a determination module, used to determine the median core particle size corresponding to the multiple wells according to the logging data corresponding to the multiple wells, and the target core data, wherein the median core particle size corresponding to the multiple wells is used to describe the rock properties of the formations of the corresponding wells; a prediction module, used to identify whether the target area has stratigraphic oil and gas reservoirs according to the median core particle size corresponding to the multiple wells.

[0016] According to another aspect of an embodiment of the present invention, a non-volatile storage medium is provided, the non-volatile storage medium including a stored program, wherein when the program is running, the device where the non-volatile storage medium is located is controlled to execute any one of the above-mentioned stratigraphic oil and gas reservoir identification methods.

[0017] According to another aspect of the embodiments of the present invention, a computer device is provided. The computer device includes a processor, and the processor is used to run a program. When the program is run, any one of the above-mentioned stratigraphic oil and gas reservoir identification methods is executed.

[0018] In an embodiment of the present invention, a method of calculating the median core grain sizes corresponding to multiple wells in the target area is adopted, by obtaining the logging data corresponding to the multiple wells included in the target area and the target core data of the target well among the multiple wells; according to the logging data corresponding to the multiple wells and the target core data, the median core grain sizes corresponding to the multiple wells are determined, wherein the median core grain sizes corresponding to the multiple wells are used to describe the rock properties of the formations of the corresponding wells; according to the median core grain sizes corresponding to the multiple wells, whether the target area has stratigraphic oil and gas reservoirs is identified, thereby achieving the purpose of identifying whether there are oil and gas reservoirs in the formations in the target area by the median core grain sizes corresponding to the multiple wells in the target area, thereby achieving the technical effect of identifying the accumulation of high mud sandstone reservoirs, and further solving the technical problem of the lack of a method for identifying the accumulation of high mud sandstone reservoirs in the related art. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0020] Figure 1 A hardware structure block diagram of a computer terminal for implementing a formation oil and gas reservoir identification method is shown;

[0021] Figure 2 is a schematic flow chart of a method for identifying oil and gas reservoirs in a formation provided in an embodiment of the present invention;

[0022] Figure 3 is a schematic diagram of visualization of median particle size provided according to an optional embodiment of the present invention;

[0023] Figure 4 is a schematic diagram of visualization analysis of well logging data provided according to an optional embodiment of the present invention;

[0024] Figure 5 It is a structural block diagram of a formation oil and gas reservoir identification device provided according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] 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.

[0026] 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.

[0027] According to an embodiment of the present invention, a method embodiment for identifying stratigraphic oil and gas reservoirs is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0028] The method embodiment provided in the first embodiment of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 1 The hardware structure block diagram of a computer terminal for implementing a formation oil and gas reservoir identification method is shown. Figure 1 As shown, the computer terminal 10 may include one or more (102a, 102b, ..., 102n are used to illustrate) processors (the processor may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0029] It should be noted that the one or more processors and / or other data processing circuits described above may generally be referred to herein as "data processing circuits". The data processing circuits may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuit may be a single independent processing module, or may be incorporated in whole or in part into any of the other components in the computer terminal 10. As described in the embodiments of the present application, the data processing circuit acts as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0030] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the formation oil and gas reservoir identification method in the embodiment of the present invention. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, the formation oil and gas reservoir identification method of the above-mentioned application program is realized. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the computer terminal 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0031] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer terminal 10 .

[0032] Figure 2 FIG. 1 is a flow chart of a method for identifying oil and gas reservoirs in a formation according to an embodiment of the present invention. Figure 2 As shown, the method comprises the following steps:

[0033] Step S202, obtaining well logging data corresponding to each of the multiple wells included in the target area, and target core data of a target well among the multiple wells.

[0034] In this step, the target area can be an area of ​​oil and gas reservoirs to be exploited. The target area includes multiple wells. The multiple wells in the target area can be measured to obtain logging data corresponding to the multiple wells. The logging data can be data measured by various well technologies. The rock characteristics at multiple depths in the well can be obtained by analyzing the logging data. The target well can be a standard well selected from multiple wells. The standard well can be a well with relatively standard logging data and relatively uniform formation rock distribution among multiple wells. Because the cost of the method for measuring the core data of the well is relatively high, it is expensive to measure the core data of each well and perform formation analysis in actual applications. Therefore, the target well can be selected from the multiple wells according to the logging data corresponding to the multiple wells, and then only the target core data of the target well can be measured. It should be noted that the target well can be one well or multiple wells.

[0035] Step S204, determining the median core particle sizes corresponding to the multiple wells respectively according to the well logging data corresponding to the multiple wells respectively and the target core data, wherein the median core particle sizes corresponding to the multiple wells respectively are used to describe the rock properties of the formations of the corresponding wells.

[0036] In this step, the relationship between the rock properties and the logging data in the formation data applicable to the target area can be analyzed based on the logging data and the target core data corresponding to the multiple wells, and then the median core grain size corresponding to the multiple wells can be determined based on the above relationship. Among them, the median core grain size is data that characterizes the rock properties of the formation of the well, which is similar to the target core data. It can also be said that the median core grain size is the core data corresponding to the multiple wells obtained based on data analysis, and the target core data is the core data obtained by measuring the well.

[0037] Step S206, identifying whether the target area has stratigraphic oil and gas reservoirs according to the median values ​​of the core grain sizes corresponding to the multiple wells.

[0038] In this step, it is possible to determine whether there is a stratigraphic oil and gas reservoir at the location corresponding to each of the multiple wells according to the median core particle size corresponding to each of the multiple wells, and then determine whether there is a stratigraphic oil and gas reservoir in the target area. When it is determined that there is a stratigraphic oil and gas reservoir in the target area, the target area can be mined.

[0039] Through the above steps, the purpose of identifying whether there are oil and gas reservoirs in the strata in the target area can be achieved by using the median core particle size corresponding to multiple wells in the target area, thereby achieving the technical effect of identifying the formation of high-mud sandstone reservoirs, and further solving the technical problem of the lack of a method for identifying the formation of high-mud sandstone reservoirs in related technologies.

[0040] As an optional embodiment, according to the well logging data corresponding to the multiple wells, and the target core data, determining the median core grain sizes corresponding to the multiple wells respectively can be achieved by the following steps: determining the well logging data corresponding to the target well as the target well logging data among the well logging data corresponding to the multiple wells respectively; determining the median grain size function of the target area according to the target well logging data and the target core data, wherein the median grain size function describes the relationship between the well logging data corresponding to the multiple wells included in the target area and the median core grain sizes; bringing the well logging data corresponding to the multiple wells respectively into the median grain size function to determine the median core grain sizes corresponding to the multiple wells respectively.

[0041] Optionally, the well logging data corresponding to the target well can be determined as the target well logging data in the well logging data corresponding to the multiple wells respectively, and then the corresponding relationship between the median core grain size in the formation data applicable to the target area and the well logging data can be analyzed based on the target well logging data and the target core data. The corresponding relationship can be expressed as a median grain size function, and then the well logging data of the wells other than the target well in the multiple wells can be brought into the median grain size function to determine the median core grain size of the wells other than the target well in the multiple wells. Among them, the median core grain size is data that characterizes the rock properties of the formation of the well, which is similar to the target core data. It can also be said that the median core grain size is the core data corresponding to the multiple wells obtained based on data analysis, and the target core data is the core data obtained by measuring the target well.

[0042] As an optional embodiment, determining the median grain size function of the target area based on the target logging data and the target core data can be achieved through the following steps: performing regression analysis on the target logging data and the target core data, and determining that the functional relationship between the target core data and the target logging data is the median grain size function.

[0043] Optionally, a linear regression analysis can be performed by analyzing the target logging data and the target core data to determine the correlation between the logging data and the core data represented by a linear function as a median particle size function. Specifically, the median particle size function can be: Md = 6.236 × (GR / GR0) - 2.7147 × (CNL / CNL0) - 1.1854), where: Md is the median particle size, in um; GR is the natural gamma data in the logging data, in API; GR0 is the natural gamma data of the standard layer in the target logging data, in API; CNL is the neutron porosity in the logging data, in %; CNL0 is the neutron porosity of the standard layer in the target logging data, in %.

[0044] As an optional embodiment, before the well logging data corresponding to the multiple wells are brought into the median grain size function to determine the median core grain sizes corresponding to the multiple wells, it can also include: determining multiple differences between the well logging data corresponding to the multiple wells and the target well logging data; and performing standardization correction on the well logging data corresponding to the multiple wells according to the multiple differences.

[0045] Optionally, before the logging data corresponding to the multiple wells are brought into the granularity median function for calculation, the logging data corresponding to the multiple wells can be standardized and corrected, and multiple differences between the logging data corresponding to the multiple wells and the target logging data can be determined respectively, and the logging data corresponding to the multiple wells can be standardized and corrected respectively through the multiple differences, and the corrected data can be brought into the granularity median function for calculation. Standardization correction can include translation correction and coefficient correction, and the translation correction can be specifically: correction value = measured value ± deviation value, and the coefficient correction can be specifically: correction value = measured value / deviation value, the measured value can be the logging data of the well actually measured, and the deviation value can be the difference between the measured value and the standard layer of the target well.

[0046] As an optional embodiment, it may also include: according to the values ​​of the median core particle sizes corresponding to the multiple wells, dividing the median core particle sizes corresponding to the multiple wells into multiple groups of data respectively located in different value intervals; setting different colors respectively to visualize the multiple groups of data.

[0047] Optionally, the median particle size corresponding to each wellbore can be visualized so that logging personnel can intuitively analyze the median particle size data and determine whether the formation in the target area has oil and gas reservoirs. The method for visualizing the median particle size can be to plot the median particle size data to form a curve, and then set multiple value ranges and multiple colors corresponding to the multiple value ranges. The area between the curve and the coordinate axis can be filled with the color corresponding to the corresponding data on the curve to obtain a visualized image. Figure 3is a schematic diagram of the visualization of the median particle size according to an optional embodiment of the present invention, such as Figure 3 As shown, the left and right sides of the rectangle can also be used as coordinate axes, and the curve of the median particle size can be used to make two identical curves in a mirror relationship, and the two areas and the areas formed by the other two sides of the rectangle can be filled with different colors using the colors corresponding to the corresponding data on the curve, so as to obtain a visual image that is convenient for logging personnel to intuitively see the lithological characteristics of the well, that is, Figure 3 In the visualization image of lithology identification, the two curves on the lithology identification image are completely consistent with the curve trend of the median grain size on the left.

[0048] As an optional embodiment, identifying whether the target area has stratigraphic oil and gas reservoirs based on the core median grain sizes corresponding to multiple wells can be achieved through the following steps: determining that the wells corresponding to the core median grain sizes that are less than the median grain size threshold are low-abundance wells, wherein the low-abundance wells are wells where the stratigraphic oil and gas reserves at their locations are lower than the exploitation threshold, and the low-abundance wells are located without stratigraphic oil and gas reservoirs.

[0049] Optionally, in geological evaluation, "source reservoir cap transport and preservation" is the most basic reservoir condition, that is, the stratum storing the reservoir should have three special physical properties of the source layer, reservoir layer and cap layer, as well as the geological structural characteristics of migration and preservation. For high mud sandstone biogas reservoirs, the median grain size can be used to represent the storage capacity of the stratum. Core data analysis confirms that the lower limit of the reservoir is silty mudstone. When the median grain size is greater than the median grain size threshold, it indicates that the stratum has a certain reservoir space, and the stratum here may have reservoirs; when the median grain size is greater than the median grain size threshold, it indicates that the stratum does not have a reservoir space, and the stratum here cannot have reservoirs and is not easy to exploit. The corresponding well is a low-abundance well. Among them, in practical applications, the median grain size threshold can be 3.25um.

[0050] As an optional embodiment, it may also include: determining the mudstone layer thickness and formation thickness corresponding to the multiple wells respectively based on the logging data corresponding to the multiple wells respectively; determining the proportion of the mudstone layer thickness corresponding to the multiple wells respectively in the formation thickness based on the mudstone layer thickness and formation thickness corresponding to the multiple wells respectively; and determining that the wells corresponding to the proportion less than the mudstone layer proportion threshold are low-abundance wells.

[0051] Optionally, for high-mud sandstone biogas reservoirs, the development of source rocks is an important basic background condition for gas sand body accumulation. Therefore, the development thickness of source rocks in the vertical direction of a single well and the proportion of mudstone layers within a certain formation thickness have excellent hydrocarbon generation capacity characterization significance. The proportion of mudstone layer thickness in the formation thickness can be used as an important indicator of source rock hydrocarbon generation. When the proportion of mudstone layer thickness in the formation thickness represented by the logging data is less than the mudstone layer proportion threshold, the corresponding well is a low-abundance well and is not easy to mine; when the proportion of mudstone layer thickness in the formation thickness represented by the logging data is less than the mudstone layer proportion threshold, the corresponding well may have accumulation in the formation. The mudstone layer proportion threshold can be 25%.

[0052] As an optional embodiment, it may also include: determining the reservoirs and cap layers corresponding to the multiple wells respectively based on the logging data corresponding to the multiple wells respectively; determining the difference between the gamma amplitude of the reservoirs and the gamma amplitude of the cap layers corresponding to the multiple wells respectively; and determining that the wells corresponding to the differences less than the gamma threshold are low-abundance wells.

[0053] Optionally, the difference between the gamma amplitude of the reservoir and the gamma amplitude of the cap layer in the logging data can also be used to represent the sealing capacity of the cap layer, that is, the physical sealing capacity. It can be determined that the wells corresponding to the difference less than the gamma threshold are low-abundance wells and are not easy to exploit; when the reservoir-cap layer gamma amplitude difference represented by the logging data is greater than the gamma threshold, the formation of the corresponding well may have reservoirs. The maximum gamma amplitude difference between the reservoir and the cap layer is 48API, and the effective lower limit is that the gamma amplitude difference is greater than 10API. Low permeability layers and low saturation layers in production are concentrated in the gamma amplitude difference range of 10-30API, so the gamma threshold can be determined to be 12API.

[0054] As an optional embodiment, the method may further include: determining reservoir property parameters corresponding to the multiple wells respectively based on the logging data corresponding to the multiple wells respectively, wherein the reservoir property parameters include at least one of the following: resistivity, acoustic wave time difference, mud content, gas saturation; and determining that the wells corresponding to the reservoir property parameters that are outside the range of the reservoir property parameters are low-abundance wells.

[0055] Optionally, the process of logging to identify reservoir fluids is generally carried out through the relationship between four properties, namely lithology, physical properties, gas content, and electrical properties. Among them, lithology is the basis for identifying reservoir fluids, and mud content is a parameter related to lithology, and can be used to determine the physical properties of reservoir fluids; physical properties are parameters that represent reservoir performance and oil and gas production capacity, and acoustic wave time difference can characterize the porosity in physical properties; the electrical properties of reservoir fluids include resistivity. In terms of fluid identification, reservoirs with different lithologies have the lowest electrical property limit value; gas saturation is the ultimate goal and core of identifying reservoir fluids. The gas saturation determines the production capacity of the well and can determine whether the reservoir has industrial mining value. The reservoir property parameter range can be resistivity>0.3Ω.m, acoustic wave>345μs / m, mud content<55%, gas saturation>38%. When the reservoir property parameters are not within the above reservoir property parameter range, it can be judged that the corresponding well is a low-abundance well and is not suitable for exploitation; when the reservoir property parameters are within the above reservoir property parameter range, the reservoir of the corresponding well is likely to have accumulation.

[0056] Specifically, in practical applications, it can be judged whether multiple well logging data corresponding to multiple wells meet the above four indicators, that is, the proportion of mudstone thickness is greater than 25%, the median particle size is greater than 3.2μm, the gamma amplitude difference is greater than 12API, and the reservoir property parameters including resistivity, acoustic wave time difference, mud content and gas saturation are all in the following ranges: resistivity>0.3Ω.m, acoustic wave>345μs / m, mud content<55%, gas saturation>38%. When the above four indicators are met, it is considered that the location of the well corresponding to the well logging data has reservoir formation and is worth mining.

[0057] As a specific embodiment, Figure 4 is a schematic diagram of visualization analysis of logging data provided according to an optional embodiment of the present invention, such as Figure 4 As shown, the logging data of wells in a certain area can be collected and analyzed. The analysis is as follows: mudstone accounts for 77.6% and has good hydrocarbon generation ability; the median particle size of 3.3um is the reservoir space; the reservoir-cap gamma amplitude difference of 16.9API can be physically sealed to form a cap layer; the resistivity of 0.72Ω.m has gas accumulation; the average thickness is 7.6m; this layer belongs to a high-mud medium-porosity low-permeability reservoir, which is a reserve-added sand body. From 2019 to 2021, the area was tested and verified successively. At present, there are 10 production wells, with an average daily gas production of 3,400 cubic meters for vertical wells and 8,900 cubic meters for horizontal wells, and a single well EUR 20 million cubic meters. The stable test production lasted for more than 150 days, with a cumulative gas production of 8.63 million cubic meters and a predicted geological reserve of 271 million cubic meters.

[0058] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0059] Through the description of the above implementation methods, those skilled in the art can clearly understand that the stratigraphic oil and gas reservoir identification method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0060] According to an embodiment of the present invention, a stratigraphic oil and gas reservoir identification device for implementing the stratigraphic oil and gas reservoir identification method is also provided. Figure 5 is a structural block diagram of a formation oil and gas reservoir identification device provided according to an embodiment of the present invention. Figure 5 As shown, the formation oil and gas reservoir identification device includes: an acquisition module 52, a determination module 54 and an identification module 56. The formation oil and gas reservoir identification device is described below.

[0061] The acquisition module 52 is used to acquire the well logging data corresponding to the multiple wells included in the target area, and the target core data of the target well among the multiple wells.

[0062] The determination module 54 is connected to the acquisition module 52, and is used to determine the median core particle size corresponding to the multiple wells according to the logging data corresponding to the multiple wells and the target core data, wherein the median core particle size corresponding to the multiple wells is used to describe the rock properties of the formations of the corresponding wells.

[0063] The identification module 56 is connected to the determination module 54 and is used to identify whether the target area has a stratigraphic oil and gas reservoir according to the median values ​​of the core grain sizes corresponding to the multiple wells.

[0064] It should be noted that the acquisition module 52, the determination module 54 and the identification module 56 correspond to steps S202 to S206 in the embodiment, and the examples and application scenarios implemented by the multiple modules and the corresponding steps are the same, but are not limited to the contents disclosed in the above embodiment. It should be noted that the above modules, as part of the device, can be run in the computer terminal 10 provided in the embodiment.

[0065] An embodiment of the present invention may provide a computer device. Optionally, in this embodiment, the computer device may be located in at least one network device among multiple network devices of a computer network. The computer device includes a memory and a processor.

[0066] Among them, the memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the stratigraphic oil and gas reservoir identification method and device in the embodiment of the present invention. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, realizing the above-mentioned stratigraphic oil and gas reservoir identification method. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include a memory remotely arranged relative to the processor, and these remote memories can be connected to the computer terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0067] The processor can call the information and application stored in the memory through the transmission device to perform the following steps:

[0068] Optionally, the processor may also execute the program code of the following steps: obtaining well logging data corresponding to each of the multiple wells included in the target area, and target core data of the target well among the multiple wells; determining the median core grain sizes corresponding to each of the multiple wells based on the well logging data corresponding to each of the multiple wells, and the target core data, wherein the median core grain sizes corresponding to each of the multiple wells are used to describe the rock properties of the formations of the corresponding wells; and identifying whether the target area has stratigraphic oil and gas reservoirs based on the median core grain sizes corresponding to each of the multiple wells.

[0069] Optionally, the processor may also execute the program code of the following steps: determining the median core grain sizes corresponding to the multiple wells respectively according to the logging data corresponding to the multiple wells respectively, and the target core data, including: determining the logging data corresponding to the target well as the target logging data among the logging data corresponding to the multiple wells respectively; determining the median grain size function of the target area according to the target logging data and the target core data, wherein the median grain size function describes the relationship between the median core grain sizes and the logging data corresponding to the multiple wells respectively included in the target area; bringing the logging data corresponding to the multiple wells respectively into the median grain size function to determine the median core grain sizes corresponding to the multiple wells respectively.

[0070] Optionally, the processor may also execute the program code of the following steps: determining the median grain size function of the target area according to the target logging data and the target core data, including: performing regression analysis on the target logging data and the target core data, and determining that the functional relationship between the target core data and the target logging data is the median grain size function.

[0071] Optionally, the processor may also execute program codes of the following steps: before the well logging data corresponding to the multiple wells are respectively substituted into the median particle size function to determine the median particle sizes of the core particles corresponding to the multiple wells respectively, it also includes: respectively determining multiple differences between the well logging data corresponding to the multiple wells and the target well logging data; and performing standardization correction on the well logging data corresponding to the multiple wells respectively according to the multiple differences.

[0072] Optionally, the processor may also execute the program code of the following steps: dividing the median core particle sizes corresponding to the multiple wells into multiple groups of data in different numerical ranges according to the values ​​of the median core particle sizes corresponding to the multiple wells; and setting different colors to visualize the multiple groups of data.

[0073] Optionally, the processor may also execute program code for the following steps: predicting the stratigraphic oil and gas reservoir reserves in the target area based on the core median grain sizes corresponding to the multiple wells, including: determining that the wells corresponding to the core median grain sizes that are less than the median grain size threshold are low-abundance wells, wherein the low-abundance wells are wells where the stratigraphic oil and gas reservoir reserves at their locations are lower than the exploitation threshold; the low-abundance wells are located at locations where there are no stratigraphic oil and gas reservoirs.

[0074] Optionally, the processor may also execute program codes of the following steps: determining the mudstone layer thickness and formation thickness corresponding to the multiple wells respectively based on the logging data corresponding to the multiple wells respectively; determining the proportion of the mudstone layer thickness corresponding to the multiple wells respectively in the formation thickness based on the mudstone layer thickness and formation thickness corresponding to the multiple wells respectively; determining that the wells corresponding to the proportions less than the mudstone layer proportion threshold are low-abundance wells.

[0075] Optionally, the processor may also execute program codes of the following steps: determining the reservoirs and cap layers corresponding to the multiple wells respectively based on the logging data corresponding to the multiple wells respectively; determining the difference between the gamma amplitude of the reservoirs and the gamma amplitude of the cap layers corresponding to the multiple wells respectively; and determining that the wells corresponding to the differences less than the gamma threshold are low-abundance wells.

[0076] Optionally, the processor may also execute program codes of the following steps: determining reservoir property parameters corresponding to the plurality of wells respectively based on logging data corresponding to the plurality of wells respectively, wherein the reservoir property parameters include at least one of the following: resistivity, acoustic wave time difference, mud content, and gas saturation; and determining that the wells corresponding to the reservoir property parameters that are outside the range of the reservoir property parameters are low-abundance wells.

[0077] By adopting the embodiment of the present invention, a solution for identifying stratigraphic oil and gas reservoirs is provided. By calculating the median values ​​of core grain sizes corresponding to multiple wells in the target area, the logging data corresponding to the multiple wells included in the target area and the target core data of the target well in the multiple wells are obtained; according to the logging data corresponding to the multiple wells and the target core data, the median values ​​of core grain sizes corresponding to the multiple wells are determined, wherein the median values ​​of core grain sizes corresponding to the multiple wells are used to describe the rock properties of the formations of the corresponding wells; according to the median values ​​of core grain sizes corresponding to the multiple wells, whether the target area has stratigraphic oil and gas reservoirs is identified, and the purpose of identifying whether there are oil and gas reservoirs in the formations in the target area by the median values ​​of core grain sizes corresponding to the multiple wells in the target area is achieved, thereby achieving the technical effect of identifying the accumulation of high shale sandstone reservoirs, and further solving the technical problem of the lack of accumulation identification methods for high shale sandstone reservoirs in the related technologies.

[0078] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing the hardware related to the terminal device through a program, and the program can be stored in a non-volatile storage medium, and the storage medium may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0079] The embodiment of the present invention further provides a non-volatile storage medium. Optionally, in this embodiment, the non-volatile storage medium can be used to store the program code executed by the formation oil and gas reservoir identification method provided by the above embodiment.

[0080] Optionally, in this embodiment, the non-volatile storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group.

[0081] Optionally, in this embodiment, the non-volatile storage medium is configured to store program codes for executing the following steps: obtaining well logging data corresponding to each of the multiple wells included in the target area, and target core data of a target well among the multiple wells; determining the median core grain sizes corresponding to each of the multiple wells based on the well logging data corresponding to each of the multiple wells, and the target core data, wherein the median core grain sizes corresponding to each of the multiple wells are used to describe the rock properties of the formations of the corresponding wells; and identifying whether the target area has stratigraphic oil and gas reservoirs based on the median core grain sizes corresponding to each of the multiple wells.

[0082] Optionally, in this embodiment, the non-volatile storage medium is configured to store program codes for executing the following steps: determining the median core grain sizes corresponding to the multiple wells respectively according to the logging data corresponding to the multiple wells respectively, and the target core data, including: determining the logging data corresponding to the target well as the target logging data among the logging data corresponding to the multiple wells respectively; determining the median grain size function of the target area according to the target logging data and the target core data, wherein the median grain size function describes the relationship between the logging data corresponding to the multiple wells respectively included in the target area and the median core grain sizes; bringing the logging data corresponding to the multiple wells respectively into the median grain size function to determine the median core grain sizes corresponding to the multiple wells respectively.

[0083] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for executing the following steps: determining the median grain size function of the target area based on the target logging data and the target core data, including: performing regression analysis on the target logging data and the target core data to determine that the functional relationship between the target core data and the target logging data is the median grain size function.

[0084] Optionally, in this embodiment, the non-volatile storage medium is configured to store program codes for executing the following steps: before the logging data corresponding to the multiple wells are respectively brought into the median grain size function to determine the median grain sizes of the cores corresponding to the multiple wells, it also includes: respectively determining multiple differences between the logging data corresponding to the multiple wells and the target logging data; and performing standardization correction on the logging data corresponding to the multiple wells respectively based on the multiple differences.

[0085] Optionally, in this embodiment, the non-volatile storage medium is configured to store program codes for executing the following steps: according to the values ​​of the median core grain sizes corresponding to the multiple wells, dividing the median core grain sizes corresponding to the multiple wells into multiple groups of data respectively located in different numerical ranges; and setting different colors to visualize the multiple groups of data.

[0086] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for executing the following steps: identifying whether the target area has stratigraphic oil and gas reservoirs based on the median core grain sizes corresponding to multiple wells, including: determining that the wells corresponding to the median core grain sizes that are less than the median grain size threshold are low-abundance wells, wherein the low-abundance wells are wells where the abundance of stratigraphic oil and gas reservoirs is lower than the exploitation threshold; the low-abundance wells are located without stratigraphic oil and gas reservoirs.

[0087] Optionally, in this embodiment, the non-volatile storage medium is configured to store program codes for executing the following steps: determining the mudstone layer thickness and the formation thickness corresponding to the multiple wells respectively based on the logging data corresponding to the multiple wells respectively; determining the proportion of the mudstone layer thickness corresponding to the multiple wells respectively in the formation thickness based on the mudstone layer thickness and the formation thickness corresponding to the multiple wells respectively; determining that the wells corresponding to the proportions less than the mudstone layer proportion threshold are low-abundance wells.

[0088] Optionally, in this embodiment, the non-volatile storage medium is configured to store program codes for executing the following steps: determining the reservoirs and cap layers corresponding to the multiple wells respectively based on the logging data corresponding to the multiple wells respectively; determining the difference between the gamma amplitude of the reservoirs and the gamma amplitude of the cap layers corresponding to the multiple wells respectively; and determining that the wells corresponding to the differences less than the gamma threshold are low-abundance wells.

[0089] Optionally, in this embodiment, the non-volatile storage medium is configured to store program codes for executing the following steps: determining reservoir property parameters corresponding to the multiple wells respectively based on logging data corresponding to the multiple wells respectively, wherein the reservoir property parameters include at least one of the following: resistivity, acoustic wave time difference, mud content, gas saturation; determining that the wells corresponding to the reservoir property parameters that are outside the range of the reservoir property parameters are low-abundance wells.

[0090] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0091] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0092] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0093] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0094] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0095] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a non-volatile storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0096] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for identifying stratigraphic oil and gas reservoirs, characterized in that: include: Acquire well logging data corresponding to each of the multiple wells included in the target area, and target core data of a target well among the multiple wells; Determine the median values ​​of the core grain sizes corresponding to the multiple wells respectively according to the well logging data corresponding to the multiple wells respectively and the target core data, wherein the median values ​​of the core grain sizes corresponding to the multiple wells respectively are used to describe the rock properties of the formations of the corresponding wells; Whether the target area has stratigraphic oil and gas reservoirs is identified based on the core particle size medians corresponding to the multiple wells.

2. The method according to claim 1, characterized in that Determining the median values ​​of the core grain sizes corresponding to the plurality of wells respectively according to the well logging data corresponding to the plurality of wells respectively and the target core data comprises: Determining the well logging data corresponding to the target well as the target well logging data among the well logging data corresponding to the plurality of wells; Determine a median grain size function of the target area according to the target well logging data and the target core data, wherein the median grain size function describes the relationship between the well logging data and the core grain size medians corresponding to the multiple wells included in the target area; The well logging data corresponding to the plurality of wells are respectively brought into the median grain size function to determine the median grain sizes of the cores corresponding to the plurality of wells respectively.

3. The method according to claim 2, characterized in that Determining the median particle size function of the target area according to the target well logging data and the target core data includes: A regression analysis is performed on the target well logging data and the target core data to determine that the functional relationship between the target core data and the target well logging data is the particle size median function.

4. The method according to claim 2, characterized in that: Before the well logging data corresponding to the plurality of wells are brought into the particle size median function to determine the core particle size medians corresponding to the plurality of wells, the method further includes: Respectively determining a plurality of differences between the well logging data corresponding to the plurality of wells and the target well logging data; According to the multiple differences, the well logging data corresponding to the multiple wells are standardized and corrected respectively.

5. The method according to any one of claims 1 to 4, characterized in that: Also includes: According to the values ​​of the median values ​​of the core grain sizes corresponding to the multiple wells, the median values ​​of the core grain sizes corresponding to the multiple wells are divided into a plurality of groups of data respectively located in different value intervals; Different colors are set respectively to visualize the multiple groups of data.

6. The method according to any one of claims 1 to 4, characterized in that Identifying whether the target area has stratigraphic oil and gas reservoirs according to the core particle size medians corresponding to the multiple wells, including: The well corresponding to the core median particle size that is less than the median particle size threshold is determined to be a low-abundance well, wherein the low-abundance well is a well where the abundance of the formation oil and gas reservoir is lower than the production threshold, and the location of the low-abundance well does not have a formation oil and gas reservoir.

7. The method according to claim 6, characterized in that Also includes: Determining the thickness of the mudstone layer and the formation thickness corresponding to the plurality of wells respectively according to the well logging data corresponding to the plurality of wells respectively; According to the thickness of the mudstone layer and the formation thickness respectively corresponding to the plurality of wells, determining the proportion of the thickness of the mudstone layer respectively corresponding to the plurality of wells in the formation thickness; The well corresponding to the proportion less than the mudstone layer proportion threshold is determined as the low-abundance well.

8. The method according to claim 6, characterized in that Also includes: Determining the reservoirs and caprocks corresponding to the plurality of wells, respectively, based on the well logging data corresponding to the plurality of wells; Determine the difference between the gamma amplitude of the reservoir and the gamma amplitude of the cap layer respectively corresponding to the plurality of wells; The wells corresponding to the difference values ​​less than the gamma threshold are determined to be the low-abundance wells.

9. The method according to claim 6, characterized in that Also includes: Determine reservoir property parameters corresponding to the plurality of wells respectively according to the well logging data corresponding to the plurality of wells respectively, wherein the reservoir property parameters include at least one of the following: resistivity, acoustic wave time difference, shale content, and gas saturation; The wells corresponding to the reservoir property parameters outside the reservoir property parameter range are determined as the low abundance wells.

10. A device for identifying oil and gas reservoirs in a stratum, characterized in that: include: An acquisition module, used to acquire well logging data corresponding to a plurality of wells included in a target area, and target core data of a target well among the plurality of wells; A determination module, configured to determine the median values ​​of the core grain sizes corresponding to the plurality of wells, respectively, based on the well logging data corresponding to the plurality of wells, respectively, and the target core data, wherein the median values ​​of the core grain sizes corresponding to the plurality of wells, respectively, are used to describe the rock properties of the formations of the corresponding wells; The identification module is used to identify whether the target area has a stratigraphic oil and gas reservoir according to the median values ​​of the core grain sizes corresponding to the multiple wells.

11. A non-volatile storage medium, characterized in that: The non-volatile storage medium includes a stored program, wherein when the program is executed, the device where the non-volatile storage medium is located is controlled to execute the method for identifying formation oil and gas reservoirs as claimed in any one of claims 1 to 9.

12. A computer device, characterized in that: include: Memory and processor, The memory stores a computer program; The processor is used to execute the computer program stored in the memory, and when the computer program is running, the processor executes the stratigraphic oil and gas reservoir identification method according to any one of claims 1 to 9.

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