Ultra-deep carbonatite sedimentary microfacies identification method and device and storage medium

Abstract

The invention belongs to the technical field of oil exploration, and particularly relates to an ultra-deep carbonatite sedimentary microfacies identification method and device and a storage medium. The method comprises the following steps: S1, acquiring a field actual measurement section, performing sedimentary microfacies identification on the field actual measurement section, and establishing a plurality of standard Fischer diagrams of different sedimentary microfacies; s2, aiming at a single well of which the sedimentary microfacies needs to be identified, dividing the single well into a plurality of three-level sequences, and identifying the three-level sequences as a whole sedimentary environment; s3, matching is carried out according to single well data and a standard Fischer diagram, and a weight chart is established; and S4, determining the sedimentary microfacies of the single well according to the weight chart. According to the method, the sedimentary microfacies of the single well are determined through the sequence and cycle characteristics of different horizon and in combination with various data of the single well, so that the internal cycle and sequence of the ultra-deep single well can be accurately identified, and the purpose of searching an ultra-deep new reservoir is achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of petroleum exploration, and in particular relates to a method, a device and a storage medium for identifying ultra-deep carbonate sedimentary microfacies. Background Art

[0002] With recent advances in ultra-deep carbonate exploration, and with the discovery and exploration of a series of deep oil fields such as Shunbei, Fuman, Puguang, and Anyue, theories such as "ternary control of carbonate reservoirs" have gradually emerged. In recent years, the Shunbei Oilfield has primarily explored ultra-deep carbonate formations exceeding 7,500-8,000 meters, but initial exploration and development efforts focused on fault zones. Research on the Shunbei Oil and Gas Field, part of Sinopec's "Deep Earth No. 1" project, revealed that its geology primarily consists of reservoirs formed by tectonic activity and multi-stage fluid transformation. However, other sedimentary microfacies reservoir types have not been thoroughly studied due to limitations in previous data.

[0003] The Chinese patent application, "A method for determining the connectivity level of tight gas reservoir sand bodies based on configuration," with publication number CN114966886B, proposes a method for determining the connectivity level of tight gas reservoir sand bodies, including the following steps: Step 1. Based on the similarity of well logging curve morphology, physical properties, and seismic attribute differences, the river channel sand body stages are divided and individual sand bodies are identified. Step 2. Based on sedimentary microfacies, the configuration units are divided. Step 3. Based on the vertical combination of configuration units, the configuration unit combinations are divided into five categories. Step 4. Through the study of the rock electrical characteristics of individual sand bodies, a map of single sand body lithofacies combination types and rhythmic structure types is established. Step 5. Based on the differences in physical properties and logging response characteristics, the lithofacies are classified into three major categories: Type I homogeneous lithofacies, Type II weakly heterogeneous lithofacies, and Type III strongly heterogeneous lithofacies. It can more efficiently and accurately evaluate the strength of tight gas reservoir heterogeneity, provide a theoretical basis for oil and gas exploration and development, and establish sand body templates. These templates can characterize the sand body combination type and model of tight gas reservoirs.

[0004] In addition, the Chinese patent publication number CN110646847B, "A method for identifying the breakpoint location of low-order faults in dense well network areas based on well logging data", proposes to calculate the fault development coefficient of the well to be identified and the two adjacent wells respectively, and then select the common depth point of the two calculated abnormal values to achieve rapid and accurate identification of the breakpoint location of low-order faults in dense well network areas.

[0005] However, the two aforementioned patents only analyze deep carbonate sedimentary facies from a mechanical perspective. Previous studies on the classification of deep carbonate sedimentary facies did not involve the identification of carbonate sedimentary facies. Sedimentary facies classification mainly relied on comparison of well logging curves with similar formations in areas such as the Tahe region, or was performed solely through identification of rock cuttings thin sections. However, due to the influence of temperature, pressure, and other drilling factors, the completeness of logging data is questionable. Furthermore, there are differences in the sedimentary environment with the Tahe region, and rock cuttings are affected by sampling intervals and retrieval conditions, which also poses accuracy issues.

[0006] Therefore, it is expected that a method can be formed to identify the microfacies of ultra-deep single-well carbonate sediments. Summary of the Invention

[0007] In order to solve the above-mentioned technical problems existing in the prior art, the present invention provides a method, device and storage medium for identifying ultra-deep carbonate sedimentary microfacies. The purpose is to establish a method for identifying sedimentary microfacies by combining the stratigraphic and cyclic characteristics of different layers with as complete a variety of data as possible, so as to accurately identify the internal cycles and stratigraphic sequences of ultra-deep single wells in real time and achieve the purpose of finding ultra-deep reservoirs.

[0008] To achieve the above object, the technical solution of the present invention is as follows:

[0009] A method for identifying ultra-deep carbonate sedimentary microfacies, comprising:

[0010] S1. Obtain field-measured profiles, identify sedimentary microfacies on the field-measured profiles, and establish multiple standard Fischer diagrams of different sedimentary microfacies;

[0011] S2. For single wells where sedimentary microfacies need to be identified, the wells are divided into multiple third-order sequences, and the third-order sequences are identified as a whole sedimentary environment;

[0012] S3, matching the single well data with the standard Fischer diagram to establish a weighted map;

[0013] S4. Determine the sedimentary microfacies of a single well based on the weighted map.

[0014] Furthermore, step S1 specifically includes: obtaining field measured profiles in the same area, determining the same time profile, identifying the sedimentary microfacies of the field measured profiles, obtaining complete field cycle and sequence characteristics, and establishing a standard Fischer diagram.

[0015] Furthermore, before dividing the multiple third-order sequences in step S2, the single well depositional environment is first determined.

[0016] Furthermore, the specific method for determining the sedimentary environment of a single well is to use the aspect ratio of the seismic response characteristic profile of the single well layer to calculate the angle α at that location using arctanα, and then determine the sedimentary environment of the single well.

[0017] Furthermore, in step S3, the single well data is matched with the standard Fischer diagram to establish a weighted map, which specifically includes:

[0018] S301. Classify the single wells into three categories based on the single well data, namely:

[0019] The first type of single well: a single well including isotope curves and electrical imaging data;

[0020] The second type of single well: a single well that only includes natural gamma curves, resistivity curves and acoustic wave curves;

[0021] The third type of single well: a single well that only includes cuttings data;

[0022] S302. For different single wells, corresponding data are selected to generate a Fischer curve diagram for the single well, the Fischer curve diagram of the single well is matched with a standard Fischer diagram, and the curve similarity between the Fischer curve diagram of the single well and the standard Fischer diagram of multiple sedimentary microfacies is determined, and the sedimentary microfacies of the single well is determined based on the curve similarity.

[0023] Furthermore, the sedimentary microfacies corresponding to the Fischer curve with the highest curve similarity is the sedimentary microfacies of a single well.

[0024] Furthermore, for the first type of single well, the water body changes are determined by the changes in the carbon isotope curve, and then the cycles are divided according to the water body changes. Then, the thickness changes of the divided multiple cycles are determined based on the electrical imaging data, and finally the Fischer curve diagram of the single well is generated.

[0025] Furthermore, for the second type of single well, based on the changes in natural gamma curves, resistivity curves and acoustic curves, combined with the identification results of rock fragments, cycles and thickness changes of multiple cycles are divided, and finally a Fischer curve diagram of the single well is generated.

[0026] Furthermore, for the third type of single well, the drilling speed and drilling pressure coring are analyzed, and combined with the lithology test data and the identification results of rock fragments, the thickness changes of cycles and multiple cycles are divided, and finally the Fischer curve diagram of the single well is generated.

[0027] Furthermore, before identifying rock fragments, rock cuttings are screened. The rock cuttings are selected at intervals of 1 m, and more than 10 rock cuttings are selected from the same location and ground into thin slices.

[0028] Furthermore, the standard Fischer diagram is expressed as follows:

[0029]

[0030] Where x represents the average period thickness, r represents the number of cycles of continuous thick or thin layers, represents the number of cycles of thick layers, and r represents the number of cycles of thin layers.

[0031] The present invention also provides an ultra-deep carbonate rock sedimentary microfacies identification device, which adopts the above-mentioned ultra-deep carbonate rock sedimentary microfacies identification method, comprising:

[0032] Acquisition module, used for field measured profiles and establishment of standard Fischer diagrams;

[0033] Classification module, used to analyze single well data and classify single wells;

[0034] The analysis module is used to analyze single well data and match them with the standard Fischer diagram to output the sedimentary microfacies of a single well.

[0035] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for identifying ultra-deep carbonate sedimentary microfacies is implemented.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] The ultra-deep carbonate sedimentary microfacies identification method, device and storage medium provided by the present invention determine the sedimentary microfacies of a single well by combining the sequence and cycle characteristics of different layers with various data of a single well. This allows for accurate identification of cycles and sequences within ultra-deep single wells, achieving the goal of finding new ultra-deep reservoirs, and realizing the refinement of sedimentary microfacies within cycles, providing a supporting basis for phase-controlled reservoir evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 Flow chart of the method of the present invention.

[0039] Figure 2 It is a device framework diagram of the present invention. DETAILED DESCRIPTION

[0040] The technical solution of the present invention will be clearly described below in conjunction with the accompanying drawings. Obviously, the described embodiments are not all embodiments of the present invention. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0041] It should be noted that, unless otherwise specifically stated, the relative arrangements of components and steps, and numerical expressions set forth in these embodiments should not be construed as limiting the scope of the present invention.

[0042] The following description of exemplary embodiments is merely illustrative and is not intended to limit the present invention, its application, or use in any sense. Technologies, methods, and apparatus known to those skilled in the art may not be discussed in detail herein, but to the extent applicable, such technologies, methods, and apparatuses should be considered part of this specification.

[0043] Example 1

[0044] The present invention provides a method for identifying ultra-deep carbonate sedimentary microfacies, such as Figure 1 Shown, including:

[0045] S1. Obtain field-measured sections at the same horizon. After confirming that they are sections of the same time, perform sedimentary microfacies identification on the field-measured sections to obtain complete field cycles (such as tidal margin cycles and subtidal cycles) and sequence characteristics, and establish multiple standard Fischer diagrams for different sedimentary microfacies.

[0046] The standard Fischer diagram is expressed as follows:

[0047]

[0048] Where x represents the average period thickness, r represents the number of cycles of continuous thick or thin layers, represents the number of cycles of thick layers, and r represents the number of cycles of thin layers.

[0049] S2. For single wells where sedimentary microfacies need to be identified, the wells are divided into multiple third-order sequences, and the third-order sequences are identified as a whole sedimentary environment;

[0050] For single wells where isochronous relationships of sedimentary microfacies layers need to be identified, the angle α at that location is first calculated using arctanα based on the aspect ratio of the seismic response characteristic profile of the carbonate rock layer. The sedimentary environment is then determined in combination with the overall background. Based on this, the single well is divided into multiple third-order sequences. The third-order sequence represents a complete transgressive-regressive sedimentary facies pattern and can be identified in the seismic data volume. The third-order sequence is identified as a relatively unified sedimentary environment, and the internal cycle combination of the third-order sequence is analyzed in detail using the single well data.

[0051] Taking the Upper Cambrian strata in Well X1 of Shunbei Oilfield as an example, cyclic division was carried out on the field measured profile, and three-order sequences were divided according to the Fischer diagram. The slope environment and angle of the strata were corresponding to the seismic characteristics and arctan was used for back calculation, which was determined to be the characteristics of the rimmed platform margin. According to the changes in carbon isotopes, one rise and fall was regarded as one third-order sequence. Compared with the field measured sequences, it was divided into 6 third-order sequences. The time relationship was consistent with the time interval of the third-order sequences, and the field third-order sequences corresponded to those of Well X1.

[0052] S3. Match the single-well data with the standard Fischer diagram to create a weighted map. This includes:

[0053] S301. Classify the single wells into three categories based on the single well data, namely:

[0054] Category 1 single well: single well with relatively complete data, that is, single well with isotope curves and electrical imaging data. Complete data can be defined as including conventional logging data, special logging data (electrical imaging logging, dipole acoustic logging), element logging, isotope curves, cuttings data, etc.

[0055] For the first type of single well, the changes in water body are determined by the changes in carbon isotope curves, and then cycles are divided according to the changes in water body. Then, the thickness changes of multiple divided cycles are determined based on electrical imaging data, and finally a Fischer curve diagram of the single well is generated.

[0056] Category II wells: Wells with partial data, including only natural gamma ray, resistivity, and acoustic curves. For these wells, the variations in these gamma, resistivity, and acoustic curves, combined with the identification of rock fragments, are used to delineate cycles and thickness variations across multiple cycles, ultimately generating a Fischer plot for the well. Gamma ray curves of specific minerals are prioritized for tertiary sequence delineation. Locations with significant variations in resistivity and acoustic curves are compared with those identified on rock fragment thin sections. After calibrating the rock fragment positions, verification is performed to identify sequences and cycles.

[0057] Category III wells: Wells containing only rock cuttings data. For Category III wells, core sampling is performed based on analysis of drilling rate and drilling pressure. Combined with lithologic testing data and identification of rock cuttings, cycles and thickness variations within multiple cycles are classified, and a Fischer plot is generated for the well. Special minerals are selected as marker layers within the cycle. Cycle types are identified based on the cycle variation curves in the Fischer plot and the relationships between the upper and lower lithologies. Cycle combinations are then classified based on this analysis.

[0058] Among them, before identifying rock fragments, rock fragments are screened first. The rock fragments are selected at a spacing of 1m. More than 10 rock fragments with clear edges and corners are selected from the same location and ground into thin sections. Through the lithologic combination, the cycle characteristics and microfacies of this section can be better reflected. However, due to the influence of their larger spacing than the logging record points, the identification of rock fragments can only be used as a marker layer for establishing special lithologies in thin sections, and thin-layer cycles of less than 1m cannot be identified.

[0059] S302. For different single wells, corresponding data are selected to generate a Fischer curve diagram for the single well, the Fischer curve diagram of the single well is matched with a standard Fischer diagram, and the curve similarity between the Fischer curve diagram of the single well and the standard Fischer diagrams of multiple sedimentary microfacies is determined. The sedimentary microfacies of the single well is determined based on the curve similarity, and the sedimentary microfacies corresponding to the Fischer curve with the highest curve similarity is the sedimentary microfacies of the single well.

[0060] Taking Well X1 as an example, for single-well cycles in ultra-deep carbonate rocks, including single-well cycles based on isotope curves and electrical imaging data, different cycle characteristics can be identified. First, special minerals are identified based on the single well, and then corresponding identification is made based on field and rock fragment thin section characteristics. Finally, the cycles are divided in combination with electrical imaging of the single well, and sedimentary microfacies are identified within the cycle.

[0061] S4. Determine the sedimentary microfacies of a single well based on the weighted map.

[0062] To identify ultra-deep carbonate sedimentary microfacies in the Shunbei area, a 1:50 scale composite histogram was used for refinement. Sequence cross-sections reveal that the tidal margin cycles of the secondary ribs are characterized by gamma-ray and resistivity curves approaching a funnel shape, with the microfacies transitioning from bottom to top from high-energy columnar binder rocks to thin layers of micrite. The acoustic transit time curve exhibits a box-like pattern, with low values at the beginning and end of the cycle. The inner tidal margin cycles are characterized by a tapered gamma-ray curve. Subtidal cycles are characterized by gamma-ray and resistivity curves approaching a box-like pattern, with the acoustic transit time curve showing a slow intermediate rise, with the microfacies transitioning from bottom to top from thrombolites or binder rocks to columnar stromatolites. Other locations with dramatic changes are areas of rapid thin-bed cycle change or affected by porosity and permeability variations. Similarly, the drilling time curve exhibits fluctuations at some cycle transition locations, primarily influenced by cycle interfaces, with slight fluctuations observed in areas with well-developed thin-bed joints in the tidal margin cycles.

[0063] Specific identification results for Well X are as follows: X1: 6726.01-6733.04 m. Core and imaging comparisons indicate dolomite (the original rock is a grain bank), with multiple centimeter-scale solution pores detected by black imaging logs. X1: 6955.62-6954.00 m. Thrombolith or algal clastic banks (10-25 cm) are present, along with light and dark laminations (3-5 cm), with well-developed framework pores and window pores. X1: 6886.00-6885.50 m. Horizontal bright layers interbedded with thin dark layers, to interbedded light and dark layers, indicate intertidal-supratidal sedimentation (tidal flat) and vertical dilatation fractures. X1: 6662.00-6663.11m, top-upper portion consisting of massive calcite-bearing dolomite, middle-upper portion consisting of a breccia zone, and lower portion consisting of a permeable zone (the breccia in the middle-upper portion is also primarily carbonate bedrock, with some siliceous lithology. The fluid in the lower permeable zone is composed of calcite + siliceous lithology, with carbonate bedrock at the edge). X1: 6588.10-6585.60m, "hummocky" (algal dolomite or wavy stromatolites in the algal layer), with high-angle dissolution fractures. X1: 6721.05-6719.15m, lower portion consisting of uniform, massive interbedded thin layers, middle portion consisting of light and dark interbedded layers to sequential grains, and upper portion consisting of medium-thick, massive or granular layers. X1: 6940.60-6939.30 m, massive grains (10 cm), to grain-bearing or cohesive (5-7 cm), to very thinly laminated (four cycles), intertidal to supratidal, with bedding-aligned pores in the middle and lower parts.

[0064] Example 2

[0065] The present invention also provides an ultra-deep carbonate rock sedimentary microfacies identification device, which adopts the ultra-deep carbonate rock sedimentary microfacies identification method provided in Example 1, such as Figure 2 Shown, including:

[0066] Acquisition module, used for field measured profiles and establishment of standard Fischer diagrams;

[0067] Classification module, used to analyze single well data and classify single wells;

[0068] The analysis module is used to analyze single well data and match them with the standard Fischer diagram to output the sedimentary microfacies of a single well.

[0069] Example 3

[0070] The present invention also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for identifying ultra-deep carbonate sedimentary microfacies provided in Example 1 is implemented.

[0071] The above specific embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to examples, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the scope of the technical solutions of the present invention, and all of these should be included in the scope of the claims of the present invention.

Claims

1. A method for identifying ultra-deep carbonate sedimentary microfacies, characterized in that: include: S1. Obtain field-measured profiles, identify sedimentary microfacies on the field-measured profiles, and establish multiple standard Fischer diagrams of different sedimentary microfacies; S2. For single wells where sedimentary microfacies need to be identified, the wells are divided into multiple third-order sequences, and the third-order sequences are identified as a whole sedimentary environment; S3, matching the single well data with the standard Fischer diagram to establish a weighted map; S4. Determine the sedimentary microfacies of a single well based on the weighted map.

2. The method for identifying ultra-deep carbonate sedimentary microfacies according to claim 1, characterized in that: Step S1 specifically includes: obtaining field measured profiles in the same area, determining the same time profile, identifying the sedimentary microfacies of the field measured profiles, obtaining complete field cycle and sequence characteristics, and establishing a standard Fischer diagram.

3. The method for identifying ultra-deep carbonate sedimentary microfacies according to claim 1, characterized in that: In step S2, before dividing the multiple third-order sequences, the single well depositional environment is first determined.

4. The method for identifying ultra-deep carbonate sedimentary microfacies according to claim 3, characterized in that: The specific method for determining the sedimentary environment of a single well is to use the aspect ratio of the seismic response characteristic profile of the single well layer to calculate the angle α at that position using arctanα, and then determine the sedimentary environment of the single well.

5. The method for identifying ultra-deep carbonate sedimentary microfacies according to claim 1, characterized in that: In step S3, the single well data is matched with the standard Fischer diagram to establish a weighted map, which specifically includes: S301. Classify the single wells into three categories based on the single well data, namely: The first type of single well: a single well including isotope curves and electrical imaging data; The second type of single well: a single well that only includes natural gamma curves, resistivity curves and acoustic wave curves; The third type of single well: a single well that only includes cuttings data; S302. For different single wells, corresponding data are selected to generate a Fischer curve diagram for the single well, the Fischer curve diagram of the single well is matched with a standard Fischer diagram, and the curve similarity between the Fischer curve diagram of the single well and the standard Fischer diagram of multiple sedimentary microfacies is determined, and the sedimentary microfacies of the single well is determined based on the curve similarity.

6. The method for identifying ultra-deep carbonate sedimentary microfacies according to claim 5, characterized in that: The sedimentary microfacies corresponding to the Fischer curve with the highest curve similarity is the sedimentary microfacies of a single well.

7. The method for identifying ultra-deep carbonate sedimentary microfacies according to claim 5, characterized in that: For the first type of single well, the changes in water body are determined by the changes in carbon isotope curves, and then cycles are divided according to the changes in water body. Then, the thickness changes of multiple divided cycles are determined based on electrical imaging data, and finally a Fischer curve diagram of the single well is generated.

8. The method for identifying ultra-deep carbonate sedimentary microfacies according to claim 5, characterized in that: For the second type of single well, based on the changes in natural gamma curves, resistivity curves and acoustic curves, combined with the identification results of rock fragments, cycles and thickness changes of multiple cycles are divided, and finally the Fischer curve diagram of the single well is generated.

9. The method for identifying ultra-deep carbonate sedimentary microfacies according to claim 5, characterized in that: For the third type of single well, the drilling speed and drilling pressure coring are analyzed. Combined with the lithology test data and the identification results of rock fragments, the thickness changes of cycles and multiple cycles are divided, and finally the Fischer curve diagram of the single well is generated.

10. The method for identifying ultra-deep carbonate sedimentary microfacies according to claim 8 or 9, characterized in that: Before identifying rock fragments, rock cuttings are screened first. The rock cuttings are selected at intervals of 1 m. More than 10 rock cuttings are selected from the same location and ground into thin slices.

11. The method for identifying ultra-deep carbonate sedimentary microfacies according to claim 1, characterized in that: The standard Fischer diagram is expressed as follows: Where x represents the average period thickness, r represents the number of cycles of continuous thick or thin layers, n1 represents the number of cycles of thick layers, and n2 represents the number of cycles of thin layers.

12. An ultra-deep carbonate rock sedimentary microfacies identification device, using the ultra-deep carbonate rock sedimentary microfacies identification method according to any one of claims 1 to 9, characterized in that: include: Acquisition module, used for field measured profiles and establishment of standard Fischer diagrams; Classification module, used to analyze single well data and classify single wells; The analysis module is used to analyze single well data and match them with the standard Fischer diagram to output the sedimentary microfacies of a single well.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for identifying ultra-deep carbonate sedimentary microfacies according to any one of claims 1 to 9 is implemented.

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