Shale bed series lithofacies distribution prediction method and device, storage medium and processor

Abstract

The invention relates to the field of geological prospecting, and discloses a shale bed series lithofacies distribution prediction method and device, a storage medium and a processor, and the method comprises the steps: carrying out the sequence interface calibration of a stratum of a target region, and building a three-stage sequence framework; performing sequence division of a quasi-sequence, a quasi-sequence group and a three-level system domain in the three-level sequence framework; performing T-R cycle division on the interior of the alignment sequence and the interior of the quasi-sequence group, and establishing a high-frequency sequence framework; establishing a fine particle deposition mode under the high-frequency sequence framework; verifying the sequence division, and determining a deep time unit based on a verification result; and on the basis of the high-frequency sequence framework, the fine-grained deposition mode and the depth-time unit, predicting shale bed series lithofacies distribution of the target area. Therefore, finer time deposition sequence division can be carried out on the shale bed series, so that the accuracy of shale bed series lithofacies distribution prediction can be improved.

Description

Technical Field

[0001] The present invention relates to the field of geological exploration technology, and in particular to a shale stratum lithofacies distribution prediction method, a shale stratum lithofacies distribution prediction device, a machine-readable storage medium and a processor. Background Art

[0002] The development of shale oil and gas is of great significance to the energy industry. Through horizontal drilling and horizontal fracturing technology, a large amount of oil and natural gas can be released and produced from shale layers. Among them, the shale formation has complex lithofacies and strong heterogeneity. The lithofacies distribution of shale formations is crucial for finding shale oil and gas "sweet spot" areas.

[0003] At present, the three-level sequence division method, organic sequence method, cyclostratigraphy, chemical stratigraphy, etc. are mostly used to divide the strata in order to predict the lithofacies distribution of shale strata.

[0004] However, due to factors such as insufficient division accuracy and questionable isochrony of the division areas, the prediction of the lithofacies distribution of shale formations is not accurate. Summary of the invention

[0005] The purpose of the present invention is to overcome the problem of inaccurate prediction of shale stratum lithofacies distribution in the prior art, and to provide a shale stratum lithofacies distribution prediction method, a shale stratum lithofacies distribution prediction device, a machine-readable storage medium and a processor.

[0006] In order to achieve the above object, the present invention provides a method for predicting facies distribution of shale formations, the method comprising:

[0007] Draw a first cross-section diagram including a seismic section and a single well drilling sequence for the target area, and draw a second cross-section diagram including a well-connected drilling sequence, and calibrate the sequence interface of the strata in the target area based on the first cross-section diagram and the second cross-section diagram to establish a three-level sequence framework;

[0008] Identify the shale strata in the target area, and divide the parasequences, parasequence groups and third-level system tracts within the third-level sequence framework according to the identification results;

[0009] According to the high-frequency sequence division marker parameters, the interior of the parasequence and the interior of the parasequence group are divided into TR cycles to establish a high-frequency sequence framework;

[0010] Based on the depositional genesis and spatiotemporal evolution of different lithofacies in the shale strata, a fine-grained sedimentary model under the high-frequency sequence framework is established;

[0011] Based on volcanic ash dating, the stratigraphic division is verified, and based on the verification results, the deep-time units are determined;

[0012] Based on the high-frequency sequence framework, the fine-grained sedimentary pattern and the deep-time unit, the shale strata lithofacies distribution in the target area is predicted.

[0013] In an embodiment of the present application, the step of calibrating the stratigraphic interface of the target area based on the first cross-sectional view and the second cross-sectional view includes:

[0014] Based on the first cross-sectional view, the second cross-sectional view and the paleontological marker strata of the target area, the strata in the target area are calibrated for sequence interfaces.

[0015] In the embodiment of the present application, the identification of the shale formation in the target area includes:

[0016] The laminations of the shale formation, the lithofacies of the shale formation, and the vertically corresponding superposition patterns of the sedimentary microfacies of the shale formation are identified.

[0017] In the embodiment of the present application, the identification of the vertically corresponding superposition patterns of the laminae of the shale strata, the lithofacies of the shale strata, and the sedimentary microfacies of the shale strata includes:

[0018] Based on the core data, thin section data, geochemical data and paleontological data of the target area, the laminations of the shale strata, the lithofacies of the shale strata and the vertically corresponding superposition patterns of the sedimentary microfacies of the shale strata are identified.

[0019] In an embodiment of the present application, the method further includes:

[0020] The high-frequency sequence division marker parameters are determined based on the cyclicity corresponding to paleoclimate changes, paleoenvironmental changes, terrigenous injection changes, lithofacies changes and lamina combination changes.

[0021] In an embodiment of the present application, the method further includes:

[0022] Based on the structure, provenance, climate, paleogeomorphology and geological events, the sedimentary causes of different lithofacies in shale strata and the temporal and spatial evolution of different lithofacies in shale strata are determined.

[0023] In the embodiment of the present application, the verification of the sequence division based on volcanic ash dating includes:

[0024] Based on volcanic ash dating, combined with geochemical data, well logging data and magnetic susceptibility data, the sedimentation rate of the high-frequency sequence in the high-frequency sequence framework is determined, and the time span of the high-frequency sequence is determined;

[0025] The sequence division is verified according to the time span of the high-frequency sequence.

[0026] The second aspect of the present application provides a shale stratum lithofacies distribution prediction device, comprising:

[0027] A sequence interface calibration module is used to draw a first cross-section diagram including a seismic section and a single well drilling sequence for a target area, and to draw a second cross-section diagram including a well-connected drilling sequence, and to calibrate the sequence interface of the strata in the target area based on the first cross-section diagram and the second cross-section diagram, and to establish a three-level sequence framework;

[0028] A sequence division module is used to identify the shale strata in the target area, and to divide the sequence into parasequences, parasequence groups and third-level system tracts within the third-level sequence framework according to the identification results;

[0029] A TR cycle division module is used to perform TR cycle division on the interior of the parasequence and the interior of the parasequence group according to the high-frequency sequence division mark parameters, and establish a high-frequency sequence framework;

[0030] A sedimentation model building module, used to establish a fine-grained sedimentation model under the high-frequency sequence framework based on the sedimentation genesis of different lithofacies of the shale strata and the spatiotemporal evolution of different lithofacies of the shale strata;

[0031] A verification module, for verifying the sequence division based on volcanic ash dating, and determining the deep time unit based on the verification result;

[0032] A prediction module is used to predict the shale strata lithofacies distribution in the target area based on the high-frequency sequence framework, the fine-grained sedimentary model and the deep-time unit.

[0033] A third aspect of the present application provides a processor configured to execute the above-mentioned shale formation lithofacies distribution prediction method.

[0034] A fourth aspect of the present application provides a machine-readable storage medium having instructions stored thereon, which, when executed by a processor, configure the processor to execute the above-mentioned shale formation lithofacies distribution prediction method.

[0035] Through the above technical scheme, the technical scheme includes: drawing a first cross-section diagram including seismic sections and single-well drilling sequences for the target area, and drawing a second cross-section diagram including connected-well drilling sequences, based on the first cross-section diagram and the second cross-section diagram, calibrating the sequence interface of the strata in the target area, and establishing a three-level sequence framework; identifying the shale strata in the target area, and dividing the parasequences, parasequence groups and three-level system domains in the three-level sequence framework according to the identification results; and dividing the shale strata in the target area according to the high-frequency sequences. The method comprises the following steps: dividing the parasequence and the parasequence group by TR cycles, establishing a high-frequency sequence framework; establishing a fine-grained sedimentary model under the high-frequency sequence framework based on the depositional genesis of different lithofacies of the shale system and the spatiotemporal evolution of different lithofacies of the shale system; verifying the sequence division based on volcanic ash dating, and determining the deep-time unit based on the verification result; and predicting the lithofacies distribution of the shale system in the target area based on the high-frequency sequence framework, the fine-grained sedimentary model and the deep-time unit. Based on the scheme provided in the embodiment of the present application, the shale system can be divided into a more refined time-sedimentary sequence, thereby improving the accuracy of the prediction of the lithofacies distribution of the shale system.

[0036] Other features and advantages of the embodiments of the present application will be described in detail in the subsequent specific implementation section. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the following specific implementations, they are used to explain the embodiments of the present application, but do not constitute a limitation on the embodiments of the present application. In the accompanying drawings:

[0038] Figure 1 A schematic diagram of a process flow of a shale formation lithofacies distribution prediction method according to an embodiment of the present application is schematically shown;

[0039] Figure 2 A seismic-drilling sequence comparison cross-section diagram according to an embodiment of the present application is schematically shown;

[0040] Figure 3 A schematic diagram of a drilling sequence well comparison cross-section according to an embodiment of the present application is shown;

[0041] Figure 4-1 , Figure 4-2 , Figure 4-3 as well as Figure 4-4 Schematically showing well logging data, geochemical data, data related to paleoclimate change, data related to paleoenvironmental change, data related to terrigenous injection change, data related to lithofacies change, and data related to laminae combination change according to an embodiment of the present application;

[0042] Figure 5A comparative cross-sectional view of a deposition-connected well according to an embodiment of the present application is schematically shown;

[0043] Figure 6 A diagram schematically shows a fine-grained sedimentation pattern diagram under a high-frequency sequence framework according to an embodiment of the present application;

[0044] Figure 7-1 , Figure 7-2 , Figure 7-3 , Figure 7-4 as well as Figure 7-5 A schematic diagram showing a comparison cross-section of a high-frequency sequence and an astronomical cycle well according to an embodiment of the present application;

[0045] Figure 8-1 as well as Figure 8-2 The corresponding standard plates of lithofacies-sedimentary phases-chemical phases-well logging phases according to the embodiments of the present application are schematically shown;

[0046] Fig. 9 A plan view schematically showing the formation thickness corresponding to a deep time unit according to an embodiment of the present application;

[0047] Fig.10 A schematic diagram of a lithologic plane distribution diagram of a deep-time unit according to an embodiment of the present application is shown;

[0048] Fig.11 A structural block diagram of a shale formation lithofacies distribution prediction device according to an embodiment of the present application is schematically shown;

[0049] Fig.12 The internal structure diagram of a computer device according to an embodiment of the present application is schematically shown.

[0050] Description of Reference Numerals

[0051] 201-sequence interface calibration module; 202-sequence division module; 203-TR cycle division module; 204-sedimentation mode construction module; 205-verification module; 206-prediction module; A01-processor; A02-network interface; A03-internal memory; A04-display screen; A05-input device; A06-non-volatile storage medium; B01-operating system; B02-computer program. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the specific implementation methods described herein are only used to illustrate and explain the embodiments of the present application, and are not used to limit the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0053] It should be noted that if the embodiments of the present application involve directional indications (such as up, down, left, right, front, back...), the directional indications are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0054] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present application, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or suggesting their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0055] As described in the background technology, currently, the three-level sequence division method, organic sequence method, cyclostratigraphy, chemical stratigraphy, etc. are mostly used to divide the strata to predict the distribution of shale strata. However, due to factors such as insufficient division accuracy and doubts about the isochronism of the division area, the prediction of the distribution of shale strata is not accurate.

[0056] In view of this, an embodiment of the present application provides a method for predicting the lithofacies distribution of shale formations, which can be used to predict the lithofacies distribution of shale formations in deep water areas of lake phases. More specifically, the method can predict the lithofacies vertical distribution and lithofacies horizontal distribution of shale formations in deep water areas of lake phases. Figure 1 As shown, the shale formation lithofacies distribution prediction method may include the following steps:

[0057] Step 101: Draw a first profile including a seismic profile and a single well drilling sequence for the target area, and draw a second profile including a connected well drilling sequence. Based on the first profile and the second profile, calibrate the sequence interface of the strata in the target area and establish a three-level sequence framework.

[0058] The target area may be a lacustrine area, that is, an area where a lake environment developed in geological history.

[0059] The first profile diagram including the seismic profile and the single well drilling sequence can also be called a seismic-drilling sequence comparison profile diagram; wherein the reflection characteristics of the seismic profile can be used to identify the sequence interface. The second profile diagram including the well-connected drilling sequence can also be called a drilling sequence-well-connected comparison profile diagram. Taking the target area as a lake phase area as an example, in the specific implementation, the first profile diagram and the second profile diagram can be drawn in the order from the edge of the basin to the inside of the basin, i.e., delta-shallow lake-semi-deep lake-deep lake area. The first profile diagram can be as follows: Figure 2 As shown, the second cross-sectional view can be as shown Figure 3 shown.

[0060] In the embodiment of the present application, the first cross-section image and the second cross-section image can be compared to calibrate the stratigraphic interface of the target area to establish a third-level sequence framework.

[0061] In practical applications, on the basis of the first cross-section and the second cross-section, the paleontological marker strata can be further combined to calibrate the stratigraphic sequence interface of the target area. That is, based on the first cross-section, the second cross-section and the paleontological marker strata of the target area, the stratigraphic sequence interface of the target area is calibrated.

[0062] In the embodiment of the present application, the stratigraphic interfaces of the target area are calibrated, and specifically, the secondary sequence interfaces and the tertiary sequence interfaces are calibrated, so as to establish a tertiary sequence framework of the target area.

[0063] The sequence framework can also be called the sequence isochronal framework, which usually includes primary sequence, secondary sequence, tertiary sequence and high-frequency sequence. The level of each sequence represents the geological process on different time scales. Among them, the primary sequence generally corresponds to a longer period in geological history, such as a time scale of tens of millions of years. The secondary sequence generally represents a time scale of millions of years. The tertiary sequence generally corresponds to a time scale of hundreds of thousands to millions of years. The high-frequency sequence generally corresponds to a time scale of tens of thousands to hundreds of thousands of years.

[0064] In the embodiment of the present application, based on step 101, a stratigraphic sequence framework with a larger time scale can be established for the target area, thereby making a basic and rough division of the stratigraphic time sedimentary sequence of the target area.

[0065] Step 102, identifying the shale strata in the target area, and dividing the stratigraphic sequences into parasequences, parasequence groups and third-level system tracts within the third-level sequence framework according to the identification results.

[0066] Herein, taking the target area as a lacustrine area as an example, the shale formations in the target area are identified, and specifically, the shale in the deep lake area in the target area is identified.

[0067] In an embodiment of the present application, identifying the shale formations in the target area may include: identifying the corresponding vertical superposition patterns of the laminations, lithofacies and sedimentary microfacies of the shale formations in the target area.

[0068] In specific implementation, traditional sequence stratigraphy and sedimentology research methods can be used to identify the corresponding vertical superposition patterns of the laminations of the shale strata in the target area, the lithofacies of the shale strata, and the sedimentary microfacies of the shale strata based on the core data, thin section data, geochemical data, and paleontological data of the target area.

[0069] More specifically, in the above-mentioned identification process, the laminations of the shale strata in the target area, the lithofacies of the shale strata, and the vertically corresponding superposition patterns of the sedimentary microfacies of the shale strata can be identified from the meter scale to the micrometer scale.

[0070] In the embodiment of the present application, a parasequence is a sedimentary sequence unit controlled by a relatively short relative sea (lake) level change within a relatively small time scale (such as tens of thousands of years). A parasequence group is used to describe a sedimentary sequence unit controlled by a relative sea (lake) level change of a relatively large time scale (such as hundreds of thousands of years). It is composed of a group of continuous parasequences with intrinsic genetic connections, usually formed by stacking of parasequences. A third-order system tract is a sedimentary sequence unit formed by the relative sea (lake) level rise and fall in the same period, usually composed of multiple parasequence groups, and the time scale is generally hundreds of thousands of years. According to the relative sea (lake) level rise and fall, the third-order system tract can be divided into multiple types: such as sea (lake) transgressive system tract, sea (lake) regression system tract, high-stand system tract and low-stand system tract. Multiple third-order system tracts reflect a three-level relative sea (lake) level rise and fall process, forming a third-order sequence. Each parasequence and parasequence group is composed of a sea (lake) transgression and sea (lake) regression (TR) cycle of the corresponding time scale.

[0071] It can be understood that based on step 102, the shale strata temporal sedimentary sequence in the target area can be further finely divided under the third-level sequence framework.

[0072] Step 103: According to the high-frequency sequence division mark parameters, the interior of the parasequence and the interior of the parasequence group are divided into TR cycles to establish a high-frequency sequence framework.

[0073] In an embodiment of the present application, the cyclicities corresponding to paleoclimate changes, paleoenvironmental changes, terrigenous injection changes, lithofacies changes, and lamina combination changes can be determined based on the logging data and geochemical data of multiple wells, and then the high-frequency sequence division marker parameters can be determined based on the cyclicities corresponding to paleoclimate changes, paleoenvironmental changes, terrigenous injection changes, lithofacies changes, and lamina combination changes.

[0074] In the above embodiments, the well logging data, geochemical data, data related to paleoclimate change, data related to paleoenvironmental change, data related to terrigenous injection change, data related to lithofacies change, and data related to laminae combination change can be as follows Figure 4-1 , Figure 4-2 , Figure 4-3 as well as Figure 4-4 As shown. Among them, Figure 4-1 Displayed are stratigraphic horizons, well logging data, geochemical data, terrigenous input data, and water environment data; Figure 4-2 The exhibits include paleoclimate change data, characteristics of lithofacies combination changes, sedimentary facies and high-frequency sequence divisions; Figure 4-3 The data on the changes in laminae combinations and key interface features of sequences are shown; Figure 4-4 for Figure 4-1 , Figure 4-2 as well as Figure 4-3 Corresponding legend.

[0075] In the above embodiment, after the above process, the high-frequency sequence division mark parameters obtained can be shown in Table 1:

[0076] Table 1 High-frequency sequence division marker parameters

[0077]

[0078] In the embodiments of the present application, the interior of the quasi-sequence and the interior of the parasequence group are divided into TR cycles, and the sequence of sedimentary events formed by the rise and fall caused by the relative sea (lake) level changes within the parasequence and the parasequence group can be determined. Taking the parasequence as an example, in a parasequence, the relative sea (lake) level changes can lead to changes in the sedimentary environment, thereby forming TR cycles within the sequence of different sedimentary lithofacies. These cycles are usually identified as continuous sedimentary units, representing the stages of rise and fall, respectively. Rising stage: During the relative sea (lake) level rise stage, the water body depth increases, the sediment supply decreases, the sediment grain size decreases, and the lithofacies also changes accordingly. Declining stage: During the relative sea (lake) level decline stage, the water body depth decreases, the sediment supply increases, the sediment grain size increases, and the lithofacies also changes accordingly.

[0079] It can be understood that based on step 103, by performing TR cycle division inside the quasi-sequence and para-sequence group, a high-frequency sequence framework is established, so that the shale strata temporal sedimentary sequence in the target area can be further divided more finely.

[0080] Step 104: establishing a fine-grained sedimentation model under the high-frequency sequence framework based on the depositional genesis of different lithofacies of the shale strata and the spatiotemporal evolution of different lithofacies of the shale strata.

[0081] In the embodiments of the present application, the depositional origin of different lithofacies of shale strata and the spatiotemporal evolution of different lithofacies of shale strata can be determined according to structure, provenance, climate, paleo-geomorphology, geological events, etc. Specifically, the transport-deposition process of fine-grained sediments can be interpreted according to structure, provenance, climate, paleo-geomorphology, geological events, etc., so as to determine the depositional origin of different lithofacies of shale strata and the spatiotemporal evolution of different lithofacies of shale strata.

[0082] In specific implementation, to establish the fine-grained sedimentary model, it is possible to first establish multiple comparative profiles of the connected sedimentary wells in the plane direction (lateral direction), and then establish a fine-grained sedimentary model under the high-frequency sequence framework based on the multiple comparative profiles in the plane direction. Among them, the comparative profiles in the multiple lateral directions reflect the superposition relationship of different types of sedimentary phases at different time scales of each well in the vertical direction, and reflect the distribution and pinch-out of the same type of sedimentary phases in different wells in the section direction within the same time scale in the lateral direction. Within a time scale, the sedimentary phase with the largest vertical thickness ratio and lateral area ratio in the comparative profiles of the sedimentary phases in multiple lateral directions is defined as the dominant sedimentary phase. Combined with data and maps such as structure, provenance, climate, paleogeology and geological events, the genetic factors and distribution range of the dominant sedimentary phase are comprehensively displayed on a three-dimensional map to obtain the fine-grained sedimentary model. The comparative profile of the connected sedimentary wells in a certain lateral direction can be as follows Figure 5 As shown in the figure, the fine-grained sedimentary pattern under the high-frequency sequence framework obtained based on the comparative profiles of sedimentary connected wells in multiple lateral directions can be shown as follows Figure 6 shown.

[0083] Step 105, verifying the stratigraphic division based on volcanic ash dating, and determining the deep-time unit based on the verification result.

[0084] Volcanic ash refers to the eruption debris with a diameter of less than 2 mm formed by volcanic explosive eruptions. In explosive volcanic activities, surrounding rocks and magma are broken into fine particles to form volcanic ash. Direct dating of volcanic ash uses the primary minerals or glass in volcanic ash to directly determine the age of volcanic ash. The main method is radiometric dating, which measures the decay time of certain radioactive isotopes, such as argon-argon method, uranium series method,

[0085] Luminescence method, etc.

[0086] In the embodiment of the present application, the time span of the high-frequency sequences in the high-frequency sequence framework can be determined based on volcanic ash dating, and then the sequence division in step 102 can be verified according to the time span of the high-frequency sequences.

[0087] In order to determine the time span of high-frequency sequences more accurately, on the basis of volcanic ash dating, we can also combine geochemical data, well logging data and magnetic susceptibility data, and use cyclostratigraphic methods to determine the sedimentation rate and sedimentation duration of high-frequency sequences in the high-frequency sequence framework, thereby determining the time span of high-frequency sequences.

[0088] Taking the target area as a lacustrine area as an example, when verifying the sequence division, the high-frequency sequence can be compared with the astronomical cycle well from the basin edge to the basin to verify whether the sequence division is accurate. Among them, the cross-sectional comparison of the high-frequency sequence and the astronomical cycle well can be as follows Figure 7-1 , Figure 7-2 , Figure 7-3 , Figure 7-4 as well as Figure 7-5 As shown. Among them, Figure 7-1 Shown are the well logging data, lithologic changes, sedimentary facies, and high-frequency sequence divisions of wells drilled in the delta-shallow lake-semi-deep lake area near the basin margin; Figure 7-2 Shown are the well logging data, lithologic changes, sedimentary facies, high-frequency sequences, and astronomical cycle divisions of wells drilled in the semi-deep lake-deep lake area near the center of the basin; Figure 7-3 The display shows the well logging data, lithology changes, geochemistry, water environment and provenance input data of the wells in the semi-deep lake-deep lake area in the center of the basin, as well as the sedimentary facies and high-frequency sequence division; Figure 7-4 Shown are the well logging data, lithologic changes, sedimentary facies, high-frequency sequences, and astronomical cycle divisions of the wells in the semi-deep lake-deep lake area in the center of the basin; Figure 7-5 Shown are the logging data, lithology changes, sedimentary facies and high-frequency sequence divisions of the wells in the semi-deep lake area of ​​the secondary depression on the eastern side of the basin.

[0089] After verifying the sequence division, deep time units can be established. For example, a deep time unit can be a parasequence group with a depositional time of about 170 kyr. At the same time, after verifying the sequence division, the dominant sedimentary facies and lithofacies can also be determined within the determined deep time unit.

[0090] Step 106: predicting the shale strata lithofacies distribution in the target area based on the high-frequency sequence framework, the fine-grained sedimentary model and the deep-time unit.

[0091] The prediction of the shale formation lithofacies distribution in the target area can be performed by drawing a plan distribution map of the shale formation lithofacies in the target area based on the high-frequency sequence framework, the fine-grained sedimentary pattern and the deep-time unit.

[0092] The specific implementation process of step 106 may include: establishing a corresponding standard plate of lithofacies-sedimentary phase-chemical phase-logging phase based on multi-well data, determining the lithofacies type, comparing lithofacies-connected wells under the high-frequency sequence framework, counting the stratigraphic thickness corresponding to the deep-time unit and the thickness of the dominant lithofacies, and compiling lithofacies plane distribution maps of different deep-time units based on the ancient sedimentary landforms and the fine-grained sedimentary model and the accuracy requirements.

[0093] Among them, the corresponding standard plates of lithofacies-sedimentary phases-chemical phases-logging phases can be as follows: Figure 8-1 and Figure 8-2 As shown. Among them, Figure 8-1 It is the standard plate corresponding to lithofacies and sedimentation; Figure 8-2 The plane diagram of the formation thickness corresponding to the deep time unit can be shown as follows: Fig. 9 As shown in Table 2, the thickness data of some fine-grained sedimentary facies corresponding to the deep-time unit can be shown in Table 2. The lithofacies plane distribution map of the deep-time unit can be shown in Table 2. Fig.10 shown.

[0094] Table 2 Thickness data of fine-grained sedimentary facies corresponding to deep-time units

[0095]

[0096]

[0097] It can be understood that the shale strata lithofacies distribution prediction method provided in the embodiment of the present application includes: drawing a first cross-sectional diagram including a seismic section and a single well drilling sequence for a target area, and drawing a second cross-sectional diagram including a well-connected drilling sequence; based on the first cross-sectional diagram and the second cross-sectional diagram, calibrating the sequence interface of the strata in the target area, and establishing a three-level sequence framework; identifying the shale strata in the target area, and performing parasequence, parasequence group and three-level system tract sequence division in the three-level sequence framework according to the identification result; division; according to the high-frequency sequence division marker parameters, the interior of the parasequence and the interior of the parasequence group are divided into TR cycles to establish a high-frequency sequence framework; based on the depositional genesis of different lithofacies of the shale strata and the spatiotemporal evolution of different lithofacies of the shale strata, a fine-grained sedimentary model under the high-frequency sequence framework is established; based on volcanic ash dating, the sequence division is verified, and based on the verification results, the deep-time unit is determined; based on the high-frequency sequence framework, the fine-grained sedimentary model and the deep-time unit, the lithofacies distribution of the shale strata in the target area is predicted. Based on the scheme provided in the embodiment of the present application, the shale strata can be divided into a more refined time-sedimentary sequence, thereby improving the accuracy of the prediction of the lithofacies distribution of the shale strata.

[0098] Through experiments, taking the Qingshankou Formation in the Songliao Basin as an example, using the shale strata lithofacies distribution prediction method provided in the above embodiment of the present application, it is possible to predict the development of 7 favorable locations for organic-rich clay shale under the high-frequency sequence framework. The measured data of TOC content (total organic carbon content) of different wells show that the prediction accuracy of the development location of organic-rich clay shale is about 71.4%, and the regions are comparable. It is predicted that there are 2 favorable areas for the distribution of organic-rich clay shale.

[0099] Figure 1 FIG. 1 is a flow chart of a method for predicting facies distribution of shale formations in one embodiment. It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0100] In one embodiment, Fig.11As shown, a shale stratum lithofacies distribution prediction device 200 is provided, comprising a sequence interface calibration module 201, a sequence division module 202, a TR cycle division module 203, a sedimentation mode construction module 204, a verification module 205 and a prediction module 206, wherein:

[0101] The sequence interface calibration module 201 is used to draw a first profile including a seismic profile and a single well drilling sequence for the target area, and to draw a second profile including a connected well drilling sequence. Based on the first profile and the second profile, the sequence interface of the strata in the target area is calibrated to establish a three-level sequence framework.

[0102] The sequence division module 202 is used to identify the shale strata in the target area and divide the shale strata into parasequences, parasequence groups and third-level system tracts within the third-level sequence framework according to the identification results.

[0103] The TR cycle division module 203 is used to perform TR cycle division on the interior of the parasequence and the interior of the parasequence group according to the high-frequency sequence division mark parameters, and establish a high-frequency sequence framework.

[0104] The deposition model building module 204 is used to establish a fine-grained deposition model under the high-frequency sequence framework based on the depositional genesis of different lithofacies of the shale strata and the spatiotemporal evolution of different lithofacies of the shale strata.

[0105] The verification module 205 is used to verify the stratigraphic division based on volcanic ash dating, and determine the deep-time unit based on the verification result.

[0106] The prediction module 206 is used to predict the shale strata lithofacies distribution in the target area based on the high-frequency sequence framework, the fine-grained sedimentary model and the deep-time unit.

[0107] In one embodiment, the sequence interface calibration module 201 is used to calibrate the sequence interface of the strata in the target area based on the first cross-sectional view, the second cross-sectional view and the paleontological marker strata in the target area.

[0108] In one embodiment, the sequence division module 202 is used to identify the vertically corresponding superposition patterns of the laminations of the shale strata, the lithofacies of the shale strata, and the sedimentary microfacies of the shale strata.

[0109] In one embodiment, the stratigraphic division module 202 is used to identify the vertically corresponding superposition patterns of the laminations of the shale strata, the lithofacies of the shale strata, and the sedimentary microfacies of the shale strata based on the core data, thin section data, geochemical data, and paleontological data of the target area.

[0110] In one embodiment, the high-frequency sequence division marker parameters are determined based on the cyclicity corresponding to paleoclimatic changes, paleoenvironmental changes, terrigenous injection changes, lithofacies changes, and lamina combination changes, respectively.

[0111] In one embodiment, the depositional origin of different lithofacies in the shale formation and the spatiotemporal evolution of different lithofacies in the shale formation are determined based on structure, provenance, climate, paleo-geomorphology and geological events.

[0112] In one embodiment, the verification module 205 is used to determine the sedimentation rate of the high-frequency sequence in the high-frequency sequence framework based on volcanic ash dating, combined with geochemical data, logging data and magnetic susceptibility data, and determine the time span of the high-frequency sequence; according to the time span of the high-frequency sequence, the sequence division is verified.

[0113] The shale stratum lithofacies distribution prediction device includes a processor and a memory. The above-mentioned sequence interface calibration module 201, sequence division module 202, TR cycle division module 203, sedimentation mode construction module 204, verification module 205 and prediction module 206 are all stored in the memory as program units, and the processor executes the above-mentioned program modules stored in the memory to realize corresponding functions.

[0114] The processor includes a kernel, which retrieves the corresponding program unit from the memory. One or more kernels can be set, and the shale stratum lithofacies distribution prediction method can be implemented by adjusting kernel parameters.

[0115] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0116] An embodiment of the present application provides a storage medium on which a program is stored. When the program is executed by a processor, the above-mentioned shale formation lithofacies distribution prediction method is implemented.

[0117] An embodiment of the present application provides a processor, which is used to run a program, wherein the program executes the above-mentioned shale formation lithofacies distribution prediction method when running.

[0118] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Fig.12As shown. The computer device includes a processor A01, a network interface A02, a display screen A04, an input device A05 and a memory (not shown in the figure) connected through a system bus. Among them, the processor A01 of the computer device is used to provide computing and control capabilities. The memory of the computer device includes an internal memory A03 and a non-volatile storage medium A06. The non-volatile storage medium A06 stores an operating system B01 and a computer program B02. The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 in the non-volatile storage medium A06. The network interface A02 of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor A01, a shale formation facies distribution prediction method is implemented. The display screen A04 of the computer device can be a liquid crystal display or an electronic ink display, and the input device A05 of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0119] Those skilled in the art will understand that Fig.12 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0120] In one embodiment, the shale formation lithofacies distribution prediction device provided in the present application can be implemented in the form of a computer program. The computer program can be used in Fig.12 The computer device is run on the computer device shown. The memory of the computer device can store various program modules constituting the shale formation lithofacies distribution prediction device, and the computer program composed of various program modules enables the processor to execute the steps of the shale formation lithofacies distribution prediction method of each embodiment of the present application described in this specification.

[0121] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0122] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0123] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0124] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0125] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0126] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0127] Computer readable media include permanent and non-permanent, removable and non-removable media, and can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0128] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0129] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for predicting facies distribution of shale formations, characterized in that: The method comprises: Draw a first cross-section diagram including a seismic section and a single well drilling sequence for the target area, and draw a second cross-section diagram including a well-connected drilling sequence, and calibrate the sequence interface of the strata in the target area based on the first cross-section diagram and the second cross-section diagram to establish a three-level sequence framework; Identify the shale strata in the target area, and divide the parasequences, parasequence groups and third-level system tracts within the third-level sequence framework according to the identification results; According to the high-frequency sequence division marker parameters, the interior of the parasequence and the interior of the parasequence group are divided into TR cycles to establish a high-frequency sequence framework; Based on the depositional genesis and spatiotemporal evolution of different lithofacies in the shale strata, a fine-grained sedimentary model under the high-frequency sequence framework is established; Based on volcanic ash dating, the stratigraphic division is verified, and based on the verification results, the deep-time units are determined; Based on the high-frequency sequence framework, the fine-grained sedimentary pattern and the deep-time unit, the shale strata lithofacies distribution in the target area is predicted.

2. The method for predicting facies distribution of shale formations according to claim 1, characterized in that: The step of calibrating the stratigraphic interface of the target area based on the first cross-sectional view and the second cross-sectional view includes: Based on the first cross-sectional view, the second cross-sectional view and the paleontological marker strata of the target area, the strata in the target area are calibrated for sequence interfaces.

3. The method for predicting facies distribution of shale formations according to claim 1, characterized in that: The identifying of the shale formations in the target area includes: The laminations of the shale formation, the lithofacies of the shale formation, and the vertically corresponding superposition patterns of the sedimentary microfacies of the shale formation are identified.

4. The method for predicting facies distribution of shale formations according to claim 3, characterized in that: The identifying of the vertically corresponding superposition patterns of the laminae of the shale strata, the lithofacies of the shale strata, and the sedimentary microfacies of the shale strata includes: Based on the core data, thin section data, geochemical data and paleontological data of the target area, the laminations of the shale strata, the lithofacies of the shale strata and the vertically corresponding superposition patterns of the sedimentary microfacies of the shale strata are identified.

5. The method for predicting facies distribution of shale formations according to claim 1, characterized in that: The method further comprises: The high-frequency sequence division marker parameters are determined based on the cyclicity corresponding to paleoclimate changes, paleoenvironmental changes, terrigenous injection changes, lithofacies changes and lamina combination changes.

6. The method for predicting facies distribution of shale formations according to claim 1, characterized in that: The method further comprises: Based on the structure, provenance, climate, paleo-geomorphology and geological events, the sedimentary causes of different lithofacies in the shale strata and the temporal and spatial evolution of different lithofacies in the shale strata are determined.

7. The method for predicting facies distribution of shale formations according to claim 1, characterized in that: The verification of the sequence division based on volcanic ash dating includes: Based on volcanic ash dating, combined with geochemical data, well logging data and magnetic susceptibility data, the sedimentation rate of the high-frequency sequence in the high-frequency sequence framework is determined, and the time span of the high-frequency sequence is determined; The sequence division is verified according to the time span of the high-frequency sequence.

8. A shale stratum lithofacies distribution prediction device, characterized in that: include: A sequence interface calibration module is used to draw a first cross-section diagram including a seismic section and a single well drilling sequence for a target area, and to draw a second cross-section diagram including a well-connected drilling sequence, and to calibrate the sequence interface of the strata in the target area based on the first cross-section diagram and the second cross-section diagram, and to establish a three-level sequence framework; A sequence division module is used to identify the shale strata in the target area, and to divide the sequence into parasequences, parasequence groups and third-level system tracts within the third-level sequence framework according to the identification results; A TR cycle division module is used to perform TR cycle division on the interior of the parasequence and the interior of the parasequence group according to the high-frequency sequence division mark parameters, and establish a high-frequency sequence framework; A sedimentation model building module, used to establish a fine-grained sedimentation model under the high-frequency sequence framework based on the sedimentation genesis of different lithofacies of the shale strata and the spatiotemporal evolution of different lithofacies of the shale strata; A verification module, for verifying the sequence division based on volcanic ash dating, and determining the deep time unit based on the verification result; A prediction module is used to predict the shale strata lithofacies distribution in the target area based on the high-frequency sequence framework, the fine-grained sedimentary model and the deep-time unit.

9. A processor, characterized in that: The method is configured to execute the shale formation lithofacies distribution prediction method according to any one of claims 1 to 7.

10. A machine-readable storage medium having instructions stored thereon, characterized in that: When the instruction is executed by a processor, the processor is configured to execute the shale formation lithofacies distribution prediction method according to any one of claims 1 to 7.

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