Prediction method and device for dominant region of deep reservoir

Abstract

The invention relates to the technical field of deep oil and gas exploration, in particular to a deep reservoir dominant region prediction method and device, and the corresponding method comprises the steps: determining a reservoir sedimentary facies diagram of a deep reservoir through the sedimentary structures and sedimentary facies of a plurality of single-well reservoirs under the constraint of a pre-generated sedimentary-structure pattern diagram of the deep reservoir; wherein the sedimentary facies is a superposed part of an early-stage high-quality facies belt and a diagenetic facies belt in a quasi-synbiotic period of the deep reservoir; determining a reservoir diagenetic phase diagram of the deep reservoir according to a pre-generated diagenetic sequence diagram of the deep reservoir, the corrosion landform partition map and the fluid system plane distribution diagram; and according to the reservoir sedimentary facies map, the reservoir diagenetic facies map, the dominant sedimentary facies and the dominant diagenetic facies, predicting the dominant region of the deep reservoir. According to the method, the viewpoint of controlling the scale high-quality reservoir by the early-stage high-quality facies belt and the quasi-synbiotic lithogenous facies belt is provided, the double-phase superimposed belt control and reservoir model is established, deep reservoir prediction is carried out, and a good effect is achieved.

Description

Technical Field

[0001] This disclosure relates to the field of petroleum geophysical exploration technology, particularly the field of deep oil and gas exploration technology, specifically to a method, apparatus, equipment, storage medium, and computer program for predicting advantageous areas of deep reservoirs. Background Technology

[0002] With breakthroughs in deep drilling and completion technologies, oil and gas exploration is advancing into the ultra-deep realm. Deep reservoirs are becoming a primary research focus for major gas discoveries, and their development and utilization are currently a research hotspot and challenge. Traditionally, it was believed that due to compaction and diagenetic cementation, the porosity of carbonate rocks gradually decreases with increasing burial depth, thus deep to ultra-deep ancient carbonate rocks lack high-quality reservoirs. However, with the discovery of multiple carbonate oil and gas fields, the lower limit of the burial depth for high-quality, large-scale reservoirs has been continuously broken. However, existing sedimentary reservoir prediction methods based on dominant facies analysis face a technical bottleneck: accurately identifying high-quality, large-scale reservoirs based on sedimentary facies remains a pressing problem. Summary of the Invention

[0003] This disclosure provides a method, apparatus, equipment, storage medium, and computer program for predicting advantageous areas of deep reservoirs. Based on the technical limitations of existing reservoir prediction methods for deep reservoirs, and starting from the characteristics of deep reservoir development, it proposes the view that early high-quality facies zones and quasi-syngenetic diagenetic facies zones control large-scale high-quality reservoirs. A dual-facies superposition zone reservoir control model is established, and deep reservoir prediction has been carried out with good results.

[0004] In a first aspect, this disclosure provides a method for predicting dominant regions of deep reservoirs, including:

[0005] Under the constraints of the pre-generated sedimentary-tectonic pattern map of the deep reservoir, the reservoir sedimentary facies map of the deep reservoir is determined by the sedimentary structure and sedimentary facies of multiple single-well reservoirs; wherein, the sedimentary facies is the part of the overlap of the early high-quality facies zone and the quasi-syngenetic diagenetic facies zone of the deep reservoir.

[0006] The reservoir diagenetic facies diagram of the deep reservoir is determined based on the pre-generated diagenetic sequence diagram, karst landform zoning diagram, and fluid system planar distribution diagram of the deep reservoir.

[0007] The dominant sedimentary facies and dominant diagenetic facies of the deep reservoir are determined based on the reservoir characteristics of drilling data and / or well profiles.

[0008] Based on the reservoir sedimentary facies diagram, the reservoir diagenetic facies diagram, the dominant sedimentary facies, and the dominant diagenetic facies, the dominant regions of the deep reservoir are predicted.

[0009] In some embodiments of this disclosure, the step of generating the sedimentary-tectonic pattern map includes:

[0010] The sedimentary-tectonic pattern of the deep reservoir is determined based on geological events during its development stage and the type of tectonic-sedimentary differentiation.

[0011] In some embodiments of this disclosure, the step of generating the diagenetic sequence map includes:

[0012] The diagenetic type, syn-sedimentary alteration type, distribution depth, and corresponding alteration intensity of the deep reservoir are determined by the well profile of the deep reservoir.

[0013] The diagenetic sequence map is generated based on the diagenetic type, the type of syn-sedimentary alteration, the distribution depth, and the corresponding alteration intensity.

[0014] In some embodiments of this disclosure, the step of generating the karst landform zoning map includes:

[0015] The dissolution geomorphology zoning map is generated based on the sedimentary paleogeography and microgeography of the deep reservoir; the dissolution geomorphology zoning map is used to characterize the top surface of the key strata of the deep reservoir.

[0016] In some embodiments of this disclosure, the step of generating the planar distribution map of the fluid system includes:

[0017] The paleofluid system evolution process and current fluid system state of the deep reservoir are determined based on the current fluid characteristics and pressure system recovery simulation process in the deep reservoir.

[0018] The fluid system planar distribution map is generated based on the ancient fluid system evolution process and the current fluid system state.

[0019] In some embodiments of this disclosure, after predicting the dominant region of the deep reservoir based on the reservoir sedimentary facies map, the reservoir diagenetic facies map, the dominant sedimentary facies, and the dominant diagenetic facies, the method further includes:

[0020] Collect the first well logging evaluation parameters and the first seismic attribute parameters corresponding to the advantageous area;

[0021] The second logging evaluation parameters and the second seismic attribute parameters of the tested wells are compared with the first logging evaluation parameters and the first seismic attribute parameters, respectively, to conduct well location verification for the advantageous area.

[0022] Secondly, this disclosure provides a device for predicting the dominant region of a deep reservoir, comprising:

[0023] The reservoir sedimentary facies diagram determination module is used to determine the reservoir sedimentary facies diagram of the deep reservoir by means of the sedimentary structure and sedimentary facies of multiple single-well reservoirs, under the constraints of a pre-generated sedimentary-tectonic pattern diagram of the deep reservoir; wherein, the sedimentary facies is the part of the overlap of the early high-quality facies zone and the quasi-syngenetic diagenetic facies zone of the deep reservoir.

[0024] The reservoir diagenetic facies diagram determination module is used to determine the reservoir diagenetic facies diagram of the deep reservoir based on the pre-generated diagenetic sequence diagram, dissolution geomorphology zoning diagram, and fluid system planar distribution diagram of the deep reservoir.

[0025] The dominant facies determination module is used to determine the dominant sedimentary facies and dominant diagenetic facies of the deep reservoir based on the reservoir characteristics of drilling data and / or well profiles.

[0026] The dominant region prediction module is used to predict the dominant regions of the deep reservoir based on the reservoir sedimentary facies map, the reservoir diagenetic facies map, the dominant sedimentary facies, and the dominant diagenetic facies.

[0027] In some embodiments of this disclosure, a device for predicting dominant regions of deep reservoirs further includes:

[0028] A sedimentary-tectonic pattern map generation module, used to generate the sedimentary-tectonic pattern map, the sedimentary-tectonic pattern map generation module comprising:

[0029] The sedimentary-tectonic pattern map generation unit is used to determine the sedimentary-tectonic pattern map of the deep reservoir based on geological events during the development stage of the deep reservoir and the type of tectonic-sedimentary differentiation.

[0030] In some embodiments of this disclosure, a device for predicting dominant regions of deep reservoirs further includes:

[0031] A diagenetic sequence map generation module is used to generate the diagenetic sequence map, the diagenetic sequence map generation module comprising:

[0032] The diagenetic type determination unit is used to determine the diagenetic type, syn-sedimentary alteration type, distribution depth, and corresponding alteration intensity of the deep reservoir through the well-connected profile of the deep reservoir;

[0033] The diagenetic sequence map generation unit is used to generate the diagenetic sequence map based on the diagenetic type, the type of syn-sedimentary alteration, the distribution depth, and the corresponding alteration intensity.

[0034] In some embodiments of this disclosure, a device for predicting dominant regions of deep reservoirs further includes:

[0035] A karst landform zoning map generation module is used to generate the karst landform zoning map. The karst landform zoning map generation module includes:

[0036] A solution geomorphology zoning map is generated based on the sedimentary paleogeography and microgeography of the deep reservoir. The solution geomorphology zoning map is used to characterize the top surface of the key strata of the deep reservoir.

[0037] In some embodiments of this disclosure, a device for predicting dominant regions of deep reservoirs further includes:

[0038] A fluid system planar distribution diagram generation module, used to generate the fluid system planar distribution diagram, the fluid system planar distribution diagram generation module comprising:

[0039] The paleofluid system evolution process determination unit is used to determine the paleofluid system evolution process and current fluid system state of the deep reservoir based on the current fluid characteristics and pressure system recovery simulation process in the deep reservoir.

[0040] The fluid system planar distribution map generation unit is used to generate the fluid system planar distribution map based on the ancient fluid system evolution process and the current fluid system state.

[0041] In some embodiments of this disclosure, a device for predicting dominant regions of deep reservoirs further includes:

[0042] The parameter acquisition module is used to acquire the first well logging evaluation parameters and the first seismic attribute parameters corresponding to the advantageous area;

[0043] The parameter comparison module is used to compare the second logging evaluation parameters and the second seismic attribute parameters of the tested wells with the first logging evaluation parameters and the first seismic attribute parameters, respectively, in order to conduct well location verification for the advantageous area.

[0044] Thirdly, this disclosure provides a computer device including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the foregoing aspects.

[0045] Fourthly, this disclosure provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the methods described in the above aspects.

[0046] Fifthly, this disclosure provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the methods described in the foregoing aspects.

[0047] This disclosure provides a method, apparatus, equipment, storage medium, and computer program for predicting dominant areas of deep reservoirs. The method for predicting dominant areas of deep reservoirs includes: First, under the constraint of a pre-generated sedimentary-tectonic pattern map of the deep reservoir, the reservoir sedimentary facies map of the deep reservoir is determined by the sedimentary structure and sedimentary facies of multiple single-well reservoirs; wherein, the sedimentary facies is the overlapping part of the early high-quality facies zone and the quasi-syngenetic diagenetic facies zone of the deep reservoir; thus, starting from the point that the dual-facies overlapping zone controls the large-scale high-quality reservoir, a dual-facies overlapping zone reservoir control model is established. Next, the reservoir diagenetic facies map of the deep reservoir is determined according to the pre-generated diagenetic sequence map, dissolution geomorphological zoning map, and fluid system planar distribution map of the deep reservoir; the dominant sedimentary facies and dominant diagenetic facies of the deep reservoir are determined according to the reservoir characteristics of drilling data and / or well profiles; finally, the dominant areas of the deep reservoir are predicted according to the reservoir sedimentary facies map, reservoir diagenetic facies map, dominant sedimentary facies, and dominant diagenetic facies.

[0048] In summary, the method provided in this disclosure addresses the shortcomings of existing methods for predicting dominant sedimentary facies in meeting the practical needs of deep reservoir exploration in basins. Based on the characteristics of deep reservoir development, it superimposes early-stage high-quality facies zones and quasi-syngenetic diagenetic facies zones to form a "two-facies superposition zone," thus determining the distribution pattern of large-scale high-quality reservoirs under deep-earth conditions. The method proposes the concept that two-facies superposition zones control large-scale high-quality reservoirs, establishes a reservoir-controlling model for two-facies superposition zones, and has achieved good results in deep reservoir prediction. Attached Figure Description

[0049] The present disclosure will be described in more detail below based on embodiments and with reference to the accompanying drawings:

[0050] Figure 1 This is a schematic flowchart of a method for predicting the dominant region of a deep reservoir, provided in an embodiment of this disclosure.

[0051] Figure 2 This is another flowchart illustrating a method for predicting the dominant region of a deep reservoir, provided in an embodiment of this disclosure.

[0052] Figure 3 This is a schematic diagram of a third process for a method of predicting the dominant region of a deep reservoir provided in an embodiment of this disclosure.

[0053] Figure 4 This is a flowchart illustrating step 600 of a method for predicting dominant regions of deep reservoirs provided in an embodiment of this disclosure.

[0054] Figure 5 This is a schematic diagram of the fourth process for a method of predicting the dominant region of a deep reservoir provided in an embodiment of this disclosure.

[0055] Figure 6This is a fifth flowchart illustrating a method for predicting dominant regions of deep reservoirs, provided as an embodiment of this disclosure.

[0056] Figure 7 This is a flowchart illustrating step 800 of a method for predicting the dominant region of a deep reservoir provided in an embodiment of this disclosure.

[0057] Figure 8 This is a sixth flowchart illustrating a method for predicting dominant regions of deep reservoirs, provided as an embodiment of the present disclosure.

[0058] Figure 9 A flowchart illustrating a method for predicting the dominant region of a deep reservoir, provided as an application example of this disclosure.

[0059] Figure 10 A flowchart illustrating step A of this public application example.

[0060] Figure 11 A flowchart illustrating step B, which is provided as an application example of this disclosure.

[0061] Figure 12 A schematic diagram of sedimentary-diagenetic processes in the Dengying Formation provided as an application example of this disclosure.

[0062] Figure 13 A schematic diagram of the paleogeography of the Dengying Formation in the Sichuan Basin, provided as an application example of this disclosure.

[0063] Figure 14 A flowchart illustrating step C, which is provided as an application example of this disclosure.

[0064] Figure 15 A schematic diagram of the reservoir development model of the Dengying Formation provided as an application example of this disclosure.

[0065] Figure 16 A flowchart illustrating step D, which is provided as an application example of this disclosure.

[0066] Figure 17 A schematic diagram of the zonal division of the Dengying Formation in the Sichuan Basin, provided as an application example of this disclosure.

[0067] Figure 18 A block diagram of a device for predicting the dominant region of a deep reservoir, provided in an embodiment of this disclosure.

[0068] In the accompanying drawings, the same parts are referred to by the same reference numerals, and the drawings are not drawn to scale. Detailed Implementation

[0069] To enable those skilled in the art to better understand the technical solutions of this disclosure, and to fully understand and implement the process of how this disclosure applies technical means to solve technical problems and achieve corresponding technical effects, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, not all embodiments. The embodiments of this disclosure and the various features within them can be combined with each other without conflict, and the resulting technical solutions are all within the protection scope of this disclosure. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort should fall within the protection scope of this disclosure.

[0070] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0071] It should be noted that the steps shown in the flowchart in 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 may be executed in a different order than that shown here.

[0072] Example 1

[0073] This disclosure provides a method for predicting the dominant region of a deep reservoir. Figure 1 This is a flowchart illustrating a method for predicting dominant regions of deep reservoirs, provided as an embodiment of this disclosure. Figure 1 As shown, a method for predicting dominant regions of deep reservoirs includes:

[0074] Step 100: Under the constraints of the pre-generated sedimentary-tectonic pattern map of the deep reservoir, the reservoir sedimentary facies map of the deep reservoir is determined by the sedimentary structure and sedimentary facies of multiple single-well reservoirs; wherein, the sedimentary facies is the part of the overlap of the early high-quality facies zone and the quasi-syngenetic diagenetic facies zone of the deep reservoir.

[0075] Step 200: Determine the reservoir diagenetic facies map of the deep reservoir based on the pre-generated diagenetic sequence map, karst landform zoning map, and fluid system planar distribution map of the deep reservoir;

[0076] Step 300: Determine the dominant sedimentary facies and dominant diagenetic facies of the deep reservoir based on the reservoir characteristics of drilling data and / or well profiles;

[0077] Step 400: Predict the dominant regions of the deep reservoir based on the reservoir sedimentary facies diagram, the reservoir diagenetic facies diagram, the dominant sedimentary facies, and the dominant diagenetic facies.

[0078] This disclosure provides a method for predicting dominant regions of deep reservoirs, comprising: First, under the constraint of a pre-generated sedimentary-tectonic pattern map of the deep reservoir, determining the reservoir sedimentary facies map of the deep reservoir through the sedimentary structure and sedimentary facies of multiple single-well reservoirs; wherein the sedimentary facies is the superposition of the early high-quality facies zone and the quasi-syngenetic diagenetic facies zone of the deep reservoir. Next, determining the reservoir diagenetic facies map of the deep reservoir based on the pre-generated diagenetic sequence map, karst geomorphological zoning map, and fluid system planar distribution map of the deep reservoir; determining the dominant sedimentary facies and dominant diagenetic facies of the deep reservoir based on the reservoir characteristics of drilling data and / or well profiles; finally, predicting the dominant regions of the deep reservoir based on the reservoir sedimentary facies map, reservoir diagenetic facies map, dominant sedimentary facies, and dominant diagenetic facies.

[0079] Because deep reservoirs have undergone multiple phases of tectonic-sedimentary evolution and exhibit complex distribution patterns, existing methods for predicting dominant sedimentary facies cannot meet the needs of actual exploration of deep reservoirs in basins. Therefore, this disclosure, based on the development characteristics of deep reservoirs, superimposes early high-quality facies zones and quasi-syngenetic diagenetic facies zones to form a "two-facies superposition zone," thereby determining the distribution pattern of large-scale high-quality reservoirs under deep-earth conditions. Furthermore, it proposes the concept that the two-facies superposition zone controls large-scale high-quality reservoirs, establishes a reservoir-controlling model for the two-facies superposition zone, and conducts deep reservoir prediction, achieving good results.

[0080] Example 2

[0081] In step 100, "deep reservoir" refers to oil and gas accumulation spaces at depths of 4500 meters or more. Additionally, "early high-quality facies zones" refer to sedimentary rock layers formed during sedimentation that possess good reservoir and permeability characteristics. These facies zones are formed under specific sedimentary conditions and have high organic matter content and good oil storage capacity.

[0082] Quasi-syngenetic diagenetic facies refer to diagenesis that occurs during or shortly after sedimentation (usually within a few million years). These facies are characterized by their diagenetic processes being almost synchronous with the sedimentary processes. They are characterized by the following: diagenesis begins before the sediments are fully consolidated, leading to changes in the physical and chemical properties of the sediments. Diagenetic types include compaction (volume reduction due to sediment gravity) and cementation (mineral infiltration and filling of pores). Hydrogeological conditions, temperature, and pressure have a significant impact on the diagenetic process.

[0083] For example, sandstone and mudstone in environments such as rivers, lakes, and tidal flats form quasi-syngenetic diagenetic facies zones because their sedimentation and diagenesis overlap in geological time.

[0084] Regarding step 200: The diagenetic sequence diagram is used to describe the various physical, chemical, and biological changes that sedimentary rocks undergo during diagenesis. These changes affect the pore structure and permeability of the rocks, thereby affecting the storage and flow of oil and gas.

[0085] Diagenetic sequence diagrams are used to understand the evolution of reservoir rock porosity, permeability, and fluid saturation. Furthermore, by analyzing the impact of diagenesis on reservoir rock properties, they can predict the distribution and storage capacity of oil and gas.

[0086] The karst landform zoning map is used to show the different landform zones formed by the dissolution of reservoir rocks by underground fluids.

[0087] By dividing the reservoir into zones based on dissolution processes, high-porosity and high-permeability reservoir areas can be identified; dissolution development zones conducive to oil and gas accumulation can be determined, and oil and gas reserves can be assessed.

[0088] The fluid system planar distribution map shows the planar distribution of underground fluids (including water, oil, and gas) and the flow paths of the fluids in the reservoir.

[0089] Regarding step 300, dominant sedimentary facies refers to the main sedimentary features or sedimentary types formed within a specific geological time period and sedimentary environment. These sedimentary facies reflect the sedimentary environment, material source, and sedimentary mechanism at that time.

[0090] Dominant diagenetic facies refers to the main diagenetic alterations and their products that a reservoir undergoes during diagenesis. These processes include compaction, cementation, dissolution, and recrystallization, which affect the reservoir's pore structure and fluid flow characteristics.

[0091] It is understandable that the advantageous area in step 400 refers to the favorable location of the deep reservoir in vertical development and the favorable zone in horizontal distribution.

[0092] Example 3

[0093] Based on the above embodiments, see Figure 2 A method for predicting dominant regions of deep reservoirs also includes:

[0094] Step 500: Generate the sedimentary-tectonic pattern map, and then step 500 includes:

[0095] The sedimentary-tectonic pattern of the deep reservoir is determined based on geological events during its development stage and the type of tectonic-sedimentary differentiation.

[0096] Specifically, this study reviews previous findings and summarizes the main geological events and tectonic-sedimentary differentiation types during the development stages of deep reservoirs, in order to compile a phased sedimentary-tectonic pattern map.

[0097] It should be noted that the aforementioned sedimentary differentiation refers to the process by which the original material of sedimentary rocks is transported and deposited, resulting in the differentiation into relatively simple sedimentary types (rocks and minerals). Sedimentary differentiation can be divided into mechanical sedimentary differentiation, chemical sedimentary differentiation, and biological sedimentary differentiation.

[0098] Based on the above embodiments, see Figure 3 A method for predicting dominant regions of deep reservoirs also includes:

[0099] Step 600: Generate the diagenetic sequence map; then, see... Figure 4 Step 600 includes:

[0100] Step 601: Determine the diagenetic type, syn-sedimentary alteration type, distribution depth, and corresponding alteration intensity of the deep reservoir through the well profile of the deep reservoir;

[0101] Step 601, diagenesis, refers to studying the diagenesis of reservoirs through typical profile dissection, clarifying the type, depth, and intensity of syn-sedimentary alteration, and compiling a diagenetic sequence map. The types of diagenesis include:

[0102] Compaction: As sediments are continuously buried, the gravity of the overlying strata reduces the porosity between sediment particles. Compaction is more pronounced in the early diagenetic stages.

[0103] Cementation: Minerals (such as calcite, quartz, etc.) precipitate in the pores, forming cement, which further reduces porosity and permeability.

[0104] Dissolution: Underground fluids dissolve some of the minerals in the reservoir, forming secondary pores, which may increase the porosity and permeability of the reservoir.

[0105] Recrystallization: During the formation of diagenesis, the original minerals undergo a reorganization of their crystal structure, accompanied by an increase in the size of the crystal grains or a change in the mineral composition.

[0106] Replacement: One mineral is gradually replaced by another, changing the mineral composition of the rock.

[0107] Co-sedimentary alteration refers to the changes that sediments undergo during or immediately after deposition. Preferably, the types of co-sedimentary alteration in step 601 include:

[0108] Bioturbation: Deposits disturbed by biological activity may disrupt the original sedimentary structure, but may also form secondary pores.

[0109] Early cementation: Before the sediments are fully consolidated, minerals brought by fluids in the sedimentary environment precipitate in the interstices of the sediments, forming early cementation.

[0110] Dehydration and consolidation: Water in the sediment is squeezed out during the deposition process, resulting in consolidation and initial compaction.

[0111] Chemical deposition: In the surface or shallow layers of sediments, chemical processes cause mineral precipitation, altering the composition and structure of the sediments.

[0112] The intensity of diagenesis and syn-sedimentary alteration varies with depth and specific geological environment. Specifically:

[0113] Weak modification: Compaction and early cementation may only have a limited effect on the reservoir, with little change in porosity.

[0114] Medium-level alteration: As the burial depth increases, the intensity of diagenesis increases, and compaction, cementation, and dissolution significantly alter the pore structure of the reservoir, resulting in substantial changes in reservoir properties.

[0115] Strong alteration: Diagenesis reaches its peak, and recrystallization, replacement, and deep dissolution may completely change the reservoir's physical properties, significantly reducing porosity or causing the development of secondary pores.

[0116] Step 602: Generate the diagenetic sequence map based on the diagenetic type, syn-sedimentary alteration type, distribution depth, and corresponding alteration intensity.

[0117] Specifically, by interpreting typical well profiles, we study the diagenesis of reservoirs, clarify the types, depths, and intensities of syn-sedimentary alteration, and compile a diagenetic sequence map.

[0118] Example 4

[0119] Based on the above embodiments, see Figure 5A method for predicting dominant regions of deep reservoirs also includes:

[0120] Step 700: Generate the karst landform zoning map. Next, step 700 includes:

[0121] The dissolution geomorphology zoning map is generated based on the sedimentary paleogeography and microgeography of the deep reservoir; the dissolution geomorphology zoning map is used to characterize the top surface of the key strata of the deep reservoir.

[0122] Specifically, a comprehensive study of sedimentary paleogeomorphology and microgeomorphology within the work area was conducted to compile a karst geomorphological zoning map of the top surface of key strata. It can be understood that sedimentary paleogeomorphology refers to the surface morphology and evolutionary characteristics of deep reservoirs within a specific region during geological history. These paleogeomorphic features were formed during sedimentation processes, reflecting the sedimentary environment and tectonic setting of the deep reservoirs at that time. Microgeomorphology refers to the smaller-scale, localized topographic features within the surface morphology of deep reservoirs. These features are usually distributed over a small area, but they have a significant impact on the pore structure, permeability, and hydrocarbon accumulation characteristics of the reservoir.

[0123] Based on the above embodiments, see Figure 6 A method for predicting dominant regions of deep reservoirs also includes:

[0124] Step 800: Generate the planar distribution diagram of the fluid system. Then, refer to... Figure 7 Step 800 includes:

[0125] Step 801: Determine the paleofluid system evolution process and current fluid system state of the deep reservoir based on the current fluid characteristics and pressure system recovery simulation process in the deep reservoir;

[0126] Step 802: Generate the planar distribution map of the fluid system based on the evolution process of the ancient fluid system and the current state of the fluid system.

[0127] Specifically, by studying fluid characteristics and pressure system reconstruction simulations, we can investigate the evolution of ancient fluid systems and the current state of fluid systems, and compile a planar distribution map of the fluid system.

[0128] Based on the above embodiments, see Figure 8 A method for predicting dominant regions of deep reservoirs, after step 400, further includes:

[0129] Step 900: Collect the first well logging evaluation parameters and the first seismic attribute parameters corresponding to the advantageous area;

[0130] Step 1000: Compare the second logging evaluation parameters and the second seismic attribute parameters of the tested well with the first logging evaluation parameters and the first seismic attribute parameters, respectively, to conduct well location verification for the advantageous area.

[0131] Specifically, in steps 900 and 1000, the logging characteristics and seismic response of high-quality reservoirs in different models are studied, appropriate logging evaluation parameters and seismic prediction methods are selected, favorable locations for the vertical development of high-quality reservoirs and favorable zones for their horizontal distribution are studied, favorable targets are selected, and well location justification is supported.

[0132] To more accurately describe geological sedimentary facies, the most suitable seismic attribute parameter, the energy half-decay attribute, is selected. That is, the first and second seismic attribute parameters are selected as the energy half-decay attribute (the relative time position at which the seismic reflected wave energy reaches 1 / 2 within a given analysis time window).

[0133] The method for obtaining the energy half-decay property is as follows: first, obtain the cumulative amplitude of each sampling point within a given time window, and then calculate the relative time position when the energy reaches 1 / 2.

[0134] This disclosure provides a method for predicting dominant regions of deep reservoirs, comprising: First, under the constraint of a pre-generated sedimentary-tectonic pattern map of the deep reservoir, determining the reservoir sedimentary facies map of the deep reservoir through the sedimentary structure and sedimentary facies of multiple single-well reservoirs; wherein the sedimentary facies is the superposition of the early high-quality facies zone and the quasi-syngenetic diagenetic facies zone of the deep reservoir. Next, determining the reservoir diagenetic facies map of the deep reservoir based on the pre-generated diagenetic sequence map, karst geomorphological zoning map, and fluid system planar distribution map of the deep reservoir; determining the dominant sedimentary facies and dominant diagenetic facies of the deep reservoir based on the reservoir characteristics of drilling data and / or well profiles; finally, predicting the dominant regions of the deep reservoir based on the reservoir sedimentary facies map, reservoir diagenetic facies map, dominant sedimentary facies, and dominant diagenetic facies.

[0135] Based on the characteristics of deep reservoir development, the method disclosed herein proposes the concept that dual-phase superposition zones control large-scale high-quality reservoirs, establishes a dual-phase superposition zone reservoir control model, and conducts deep reservoir prediction based on this model, achieving good results.

[0136] Example 5

[0137] To further illustrate the solution, based on the above embodiments, this embodiment takes the Sichuan Basin as an example. See [link to relevant documentation]. Figure 9 This paper provides an application example to further explain a method for predicting the dominant region of deep reservoirs.

[0138] The Sichuan Basin's Sinian gas reservoirs exhibit diverse types, reservoir types, and accumulation models, indicating significant exploration potential. Four gas fields—Weiyuan, Ziyang, Anyue, and Penglai—have been discovered. Currently, multiple exploratory wells have been deployed in the Dengying Formation to explore accumulation conditions in different zones. Both breakthroughs and setbacks in exploration highlight the urgent need to identify large-scale, high-quality reservoirs, particularly focusing on how to explore the platform margin zone and break through the intra-platform zone—both key challenges and key areas of focus.

[0139] A: Determine the sedimentary structure and sedimentary differentiation of deep reservoirs.

[0140] Specifically, see Figure 10 Step A includes:

[0141] A1: Review previous research findings, summarize the main geological events and tectonic-sedimentary differentiation processes in the development stages of deep reservoirs, and compile a phased sedimentary-tectonic pattern map;

[0142] A2: Through typical well drilling and field profile analysis, the sedimentary structure and sedimentary facies of single-layer reservoirs are studied;

[0143] A3: Through well-connected profile comparison and backbone profile interpretation, analyze the structural types of reservoir development in different regions and study sedimentary filling patterns; and

[0144] A4: Conduct a comprehensive study on the reservoir distribution patterns under the dominant sedimentary facies conditions, summarize the dominant sedimentary facies controlling the reservoir, and compile a variable-scale reservoir sedimentary facies map. See Tables 1, 2, and 3.

[0145] Table 1. Summary of Major Geological Events and Tectonic-Sedimentary Differentiation in the Sinian Period

[0146]

[0147] Table 2. Summary of basic characteristics of reservoir models in the Dengying Group fractured platform margin zone.

[0148]

[0149]

[0150] Table 3. Summary of Comprehensive Analysis of the Development and Distribution of Large-Scale Reservoirs in the Dengying Formation of the Sichuan Basin

[0151]

[0152] B: Determine the syn-sedimentary alteration and karst zoning of deep reservoirs.

[0153] Specifically, see Figure 11 Step B includes:

[0154] B1: Study the diagenesis of reservoirs by interpreting the results of typical profiles, clarify the type, distribution depth and intensity of syn-sedimentary alteration, and compile a diagenetic sequence map;

[0155] B2: Conduct a comprehensive study of sedimentary paleogeography and microgeography, and compile a karst landform zoning map of the top surface of key strata;

[0156] B3: By studying fluid characteristics and pressure system reconstruction simulation, we will investigate the evolution of ancient fluid systems and the current state of fluid systems, and compile a planar distribution map of the fluid system;

[0157] B4: A comprehensive study of reservoir distribution patterns under diagenetic facies-dominant conditions was conducted, and the dominant diagenetic facies controlling reservoir formation were summarized to compile variable-scale reservoir diagenetic facies maps. See Tables 2 and 3. Figure 12 as well as Figure 13 .

[0158] C: Determine the main controlling factors and development patterns of high-quality reservoirs.

[0159] Specifically, see Figure 14 Step C includes:

[0160] C1: Statistical analysis of reservoir characteristics in different wells or profiles to summarize reservoir development types;

[0161] C2: Combining profile characteristics from different directions, comprehensively analyze the dominant sedimentary facies and dominant diagenetic facies that control high-quality reservoirs, and establish a reservoir distribution model;

[0162] C3: Based on the aforementioned research, evaluate the contribution of the controlling factors in different models, see Tables 2 and 3. Figure 15 .

[0163] D: Determine the location and distribution zone of deep reservoirs.

[0164] Specifically, see Figure 16 Step D includes:

[0165] D1: Study the logging characteristics and seismic response of high-quality reservoirs in different models;

[0166] D2: Select appropriate well logging evaluation parameters and seismic prediction methods to study the favorable locations for the vertical development of high-quality reservoirs and the favorable zones for their horizontal distribution.

[0167] D3: Select favorable targets and support well location justification; see Tables 2 and 3. Figure 15 as well as Figure 17 .

[0168] Using the methods provided in this disclosure, and based on a comprehensive review of recent exploration progress, this study investigated the major geological events and tectonic-sedimentary differentiation in the Sinian period of the Sichuan Basin. It summarized three models for the development of large-scale high-quality reservoirs and proposed a new understanding that "dual-facies superimposed zones" controlled the distribution of large-scale high-quality reservoirs. The study posits that under the control of plate boundary forces, a strong tectonic-sedimentary differentiation response occurred within the Sichuan Craton. The main geological events of the Sinian period included block faulting, syn-sedimentary uplift, and quasi-syn-sedimentary dissolution, which established different tectonic-sedimentary differentiation patterns and controlled different reservoir development models. Block faulting controlled the distribution of multi-stage platform margin zones, exhibiting a rift platform margin zone model; syn-sedimentary uplift differentiation controlled the large-scale distribution of intra-platform hillocks and shoals, exhibiting an intra-platform hillock and shoal model; and quasi-syn-sedimentary dissolution differentiation controlled the stratification and zonation of porous reservoirs, exhibiting a superimposed karst zone model.

[0169] Based on comprehensive analysis, this paper proposes that the original high-energy facies zone is the foundation for the development of large-scale high-quality reservoirs; the quasi-syngenetic zonal karstification caused by tectonic uplift is the key to the quality classification and spatial location of large-scale high-quality reservoirs. The superposition of early high-quality facies zones and quasi-syngenetic diagenetic facies zones constitutes a "dual-facies superposition zone," which determines the distribution pattern of large-scale high-quality reservoirs.

[0170] In summary, this disclosure addresses the shortcomings of existing methods for predicting dominant sedimentary facies in meeting the practical needs of deep reservoir exploration in basins. Based on the characteristics of deep reservoir development, it superimposes early-stage high-quality facies zones and quasi-syngenetic diagenetic facies zones to form a "two-facies superposition zone," thus determining the distribution pattern of large-scale high-quality reservoirs under deep-earth conditions. The disclosure proposes the concept that two-facies superposition zones control large-scale high-quality reservoirs, establishes a reservoir-controlling model for two-facies superposition zones, and conducts deep reservoir prediction, achieving good results.

[0171] Example 6

[0172] Based on the same inventive concept, this application also provides a device for predicting the dominant region of deep reservoirs, which can be used to implement the method described in the above embodiments, as shown in the following embodiments. Since the principle of the device for predicting the dominant region of deep reservoirs is similar to that of the method for predicting the dominant region of deep reservoirs, the implementation of the device for predicting the dominant region of deep reservoirs can refer to the implementation of the method for predicting the dominant region of deep reservoirs, and repeated details will not be elaborated further. As used below, the terms "unit" or "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the system described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0173] Embodiments of the present invention provide a specific implementation of a deep reservoir dominance region prediction device capable of realizing a method for predicting deep reservoir dominance regions, wherein, see [link to implementation details]. Figure 18A device for predicting dominant regions of deep reservoirs includes:

[0174] The reservoir sedimentary facies diagram determination module 10 is used to determine the reservoir sedimentary facies diagram of the deep reservoir by means of the sedimentary structure and sedimentary facies of multiple single-well reservoirs under the constraints of a pre-generated sedimentary-tectonic pattern diagram of the deep reservoir; wherein, the sedimentary facies is the part of the overlap of the early high-quality facies zone and the quasi-syngenetic diagenetic facies zone of the deep reservoir.

[0175] The reservoir diagenetic facies diagram determination module 20 is used to determine the reservoir diagenetic facies diagram of the deep reservoir based on the pre-generated diagenetic sequence diagram, dissolution geomorphology zoning diagram and fluid system planar distribution diagram of the deep reservoir.

[0176] The dominant facies determination module 30 is used to determine the dominant sedimentary facies and dominant diagenetic facies of the deep reservoir based on the reservoir characteristics of drilling data and / or well profiles.

[0177] The dominant region prediction module 40 is used to predict the dominant region of the deep reservoir based on the reservoir sedimentary facies map, the reservoir diagenetic facies map, the dominant sedimentary facies, and the dominant diagenetic facies.

[0178] In some embodiments of this disclosure, a device for predicting dominant regions of deep reservoirs further includes:

[0179] A sedimentary-tectonic pattern map generation module, used to generate the sedimentary-tectonic pattern map, the sedimentary-tectonic pattern map generation module comprising:

[0180] The sedimentary-tectonic pattern map generation unit is used to determine the sedimentary-tectonic pattern map of the deep reservoir based on geological events during the development stage of the deep reservoir and the type of tectonic-sedimentary differentiation.

[0181] In some embodiments of this disclosure, a device for predicting dominant regions of deep reservoirs further includes:

[0182] A diagenetic sequence map generation module is used to generate the diagenetic sequence map, the diagenetic sequence map generation module comprising:

[0183] The diagenetic type determination unit is used to determine the diagenetic type, syn-sedimentary alteration type, distribution depth, and corresponding alteration intensity of the deep reservoir through the well-connected profile of the deep reservoir;

[0184] The diagenetic sequence map generation unit is used to generate the diagenetic sequence map based on the diagenetic type, the type of syn-sedimentary alteration, the distribution depth, and the corresponding alteration intensity.

[0185] In some embodiments of this disclosure, a device for predicting dominant regions of deep reservoirs further includes:

[0186] A karst landform zoning map generation module is used to generate the karst landform zoning map. The karst landform zoning map generation module includes:

[0187] A solution geomorphology zoning map is generated based on the sedimentary paleogeography and microgeography of the deep reservoir. The solution geomorphology zoning map is used to characterize the top surface of the key strata of the deep reservoir.

[0188] In some embodiments of this disclosure, a device for predicting dominant regions of deep reservoirs further includes:

[0189] A fluid system planar distribution diagram generation module, used to generate the fluid system planar distribution diagram, the fluid system planar distribution diagram generation module comprising:

[0190] The paleofluid system evolution process determination unit is used to determine the paleofluid system evolution process and current fluid system state of the deep reservoir based on the current fluid characteristics and pressure system recovery simulation process in the deep reservoir.

[0191] The fluid system planar distribution map generation unit is used to generate the fluid system planar distribution map based on the ancient fluid system evolution process and the current fluid system state.

[0192] In some embodiments of this disclosure, a device for predicting dominant regions of deep reservoirs further includes:

[0193] The parameter acquisition module is used to acquire the first well logging evaluation parameters and the first seismic attribute parameters corresponding to the advantageous area;

[0194] The parameter comparison module is used to compare the second logging evaluation parameters and the second seismic attribute parameters of the tested wells with the first logging evaluation parameters and the first seismic attribute parameters, respectively, in order to conduct well location verification for the advantageous area.

[0195] This disclosure provides a device for predicting the dominant region of a deep reservoir, comprising: a reservoir sedimentary facies map determination module, used to determine the reservoir sedimentary facies map of a deep reservoir by means of the sedimentary structure and sedimentary facies of multiple single-well reservoirs under the constraints of a pre-generated sedimentary-tectonic pattern map of the deep reservoir; wherein the sedimentary facies is the superposition of the early high-quality facies zone and the quasi-syngenetic diagenetic facies zone of the deep reservoir; a reservoir diagenetic facies map determination module, used to determine the reservoir diagenetic facies map of the deep reservoir based on a pre-generated diagenetic sequence map, a karst geomorphological zoning map, and a fluid system planar distribution map of the deep reservoir; a dominant facies determination module, used to determine the dominant sedimentary facies and dominant diagenetic facies of the deep reservoir based on the reservoir characteristics of drilling data and / or well profiles; and a dominant region prediction module, used to predict the dominant region of the deep reservoir based on the reservoir sedimentary facies map, the reservoir diagenetic facies map, the dominant sedimentary facies, and the dominant diagenetic facies.

[0196] In summary, this disclosure addresses the shortcomings of existing methods for predicting dominant sedimentary facies in meeting the practical needs of deep reservoir exploration in basins. Based on the characteristics of deep reservoir development, it superimposes early-stage high-quality facies zones and quasi-syngenetic diagenetic facies zones to form a "two-facies superposition zone," thus determining the distribution pattern of large-scale high-quality reservoirs under deep-earth conditions. The disclosure proposes the concept that two-facies superposition zones control large-scale high-quality reservoirs, establishes a reservoir-controlling model for two-facies superposition zones, and conducts deep reservoir prediction, achieving good results.

[0197] Example 7

[0198] Based on the above embodiments, this embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the above embodiments.

[0199] In some embodiments of this example, a computer-readable storage medium is provided, on which a computer program is stored. When executed by a processor, the computer program implements the steps of the method described in the above embodiments, specifically including the following:

[0200] Under the constraints of the pre-generated sedimentary-tectonic pattern map of the deep reservoir, the reservoir sedimentary facies map of the deep reservoir is determined by the sedimentary structure and sedimentary facies of multiple single-well reservoirs; wherein, the sedimentary facies is the part of the overlap of the early high-quality facies zone and the quasi-syngenetic diagenetic facies zone of the deep reservoir.

[0201] The reservoir diagenetic facies diagram of the deep reservoir is determined based on the pre-generated diagenetic sequence diagram, karst landform zoning diagram, and fluid system planar distribution diagram of the deep reservoir.

[0202] The dominant sedimentary facies and dominant diagenetic facies of the deep reservoir are determined based on the reservoir characteristics of drilling data and / or well profiles.

[0203] Based on the reservoir sedimentary facies diagram, the reservoir diagenetic facies diagram, the dominant sedimentary facies, and the dominant diagenetic facies, the dominant regions of the deep reservoir are predicted.

[0204] In some embodiments of this disclosure, the step of generating the sedimentary-tectonic pattern map includes:

[0205] The sedimentary-tectonic pattern of the deep reservoir is determined based on geological events during its development stage and the type of tectonic-sedimentary differentiation.

[0206] In some embodiments of this disclosure, the step of generating the diagenetic sequence map includes:

[0207] The diagenetic type, syn-sedimentary alteration type, distribution depth, and corresponding alteration intensity of the deep reservoir are determined by the well profile of the deep reservoir.

[0208] The diagenetic sequence map is generated based on the diagenetic type, the type of syn-sedimentary alteration, the distribution depth, and the corresponding alteration intensity.

[0209] In some embodiments of this disclosure, the step of generating the karst landform zoning map includes:

[0210] The dissolution geomorphology zoning map is generated based on the sedimentary paleogeography and microgeography of the deep reservoir; the dissolution geomorphology zoning map is used to characterize the top surface of the key strata of the deep reservoir.

[0211] In some embodiments of this disclosure, the step of generating the planar distribution map of the fluid system includes:

[0212] The paleofluid system evolution process and current fluid system state of the deep reservoir are determined based on the current fluid characteristics and pressure system recovery simulation process in the deep reservoir.

[0213] The fluid system planar distribution map is generated based on the ancient fluid system evolution process and the current fluid system state.

[0214] In some embodiments of this disclosure, after predicting the dominant region of the deep reservoir based on the reservoir sedimentary facies map, the reservoir diagenetic facies map, the dominant sedimentary facies, and the dominant diagenetic facies, the method further includes:

[0215] Collect the first well logging evaluation parameters and the first seismic attribute parameters corresponding to the advantageous area;

[0216] The second logging evaluation parameters and the second seismic attribute parameters of the tested wells are compared with the first logging evaluation parameters and the first seismic attribute parameters, respectively, to conduct well location verification for the advantageous area.

[0217] In some embodiments of this example, a computer program product is provided, including a computer program / instructions, which, when executed by a processor, implements the steps of the method described in the above embodiments, specifically including the following:

[0218] Under the constraints of the pre-generated sedimentary-tectonic pattern map of the deep reservoir, the reservoir sedimentary facies map of the deep reservoir is determined by the sedimentary structure and sedimentary facies of multiple single-well reservoirs; wherein, the sedimentary facies is the part of the overlap of the early high-quality facies zone and the quasi-syngenetic diagenetic facies zone of the deep reservoir.

[0219] The reservoir diagenetic facies diagram of the deep reservoir is determined based on the pre-generated diagenetic sequence diagram, karst landform zoning diagram, and fluid system planar distribution diagram of the deep reservoir.

[0220] The dominant sedimentary facies and dominant diagenetic facies of the deep reservoir are determined based on the reservoir characteristics of drilling data and / or well profiles.

[0221] Based on the reservoir sedimentary facies diagram, the reservoir diagenetic facies diagram, the dominant sedimentary facies, and the dominant diagenetic facies, the dominant regions of the deep reservoir are predicted.

[0222] The processor may include, but is not limited to, one or more processors or microprocessors. Each processor may be implemented as an Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), controller, microcontroller, microprocessor, or other electronic component, for executing the methods in the above embodiments.

[0223] Computer-readable storage media can be implemented by any type of volatile or non-volatile storage device or a combination thereof. Computer-readable storage media may include, but are not limited to, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, and computer storage media (e.g., hard disks, floppy disks, solid-state drives, removable disks, CD-ROMs, DVD-ROMs, Blu-ray discs, etc.).

[0224] Computer-readable storage media may also store at least one computer-executable program / instruction, such as computer-readable instructions. Computer-readable storage media include, but are not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Computer-readable storage media may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, a non-transitory computer-readable storage medium may be connected to a computing device such as a computer, and then, when the computing device executes the computer-readable instructions stored on the computer-readable storage medium, the various methods described above can be performed.

[0225] In addition, the computer device may include (but is not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (e.g., keyboard, mouse, speakers, etc.).

[0226] The processor can communicate with external devices via the I / O bus through wired or wireless networks.

[0227] In one embodiment, the at least one computer-executable instruction may also be compiled into or comprise a software product / computer program product, wherein one or more computer-executable instructions are executed by a processor to perform the steps of the various functions and / or methods in the embodiments described herein.

[0228] In the embodiments provided in this disclosure, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0229] It should be noted that, in this disclosure, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element limited by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0230] While the embodiments disclosed herein are as described above, the foregoing content is merely for the purpose of facilitating understanding of this disclosure and is not intended to limit this disclosure. Any person skilled in the art to which this disclosure pertains may make any modifications and changes in form and detail of the implementation without departing from the spirit and scope of this disclosure; however, the scope of patent protection of this disclosure shall still be determined by the scope defined in the appended claims.

Claims

1. A method for predicting dominant regions of deep reservoirs, characterized in that, include: Under the constraints of the pre-generated sedimentary-tectonic pattern map of the deep reservoir, the reservoir sedimentary facies map of the deep reservoir is determined by the sedimentary structure and sedimentary facies of multiple single-well reservoirs; wherein, the sedimentary facies is the part of the overlap of the early high-quality facies zone and the quasi-syngenetic diagenetic facies zone of the deep reservoir. The reservoir diagenetic facies diagram of the deep reservoir is determined based on the pre-generated diagenetic sequence diagram, karst landform zoning diagram, and fluid system planar distribution diagram of the deep reservoir. The dominant sedimentary facies and dominant diagenetic facies of the deep reservoir are determined based on the reservoir characteristics of drilling data and / or well profiles. Based on the reservoir sedimentary facies diagram, the reservoir diagenetic facies diagram, the dominant sedimentary facies, and the dominant diagenetic facies, the dominant regions of the deep reservoir are predicted.

2. The prediction method according to claim 1, characterized in that, The steps for generating the sedimentary-tectonic pattern map include: The sedimentary-tectonic pattern of the deep reservoir is determined based on geological events during its development stage and the type of tectonic-sedimentary differentiation.

3. The prediction method according to claim 1, characterized in that, The steps for generating the diagenetic sequence map include: The diagenetic type, syn-sedimentary alteration type, distribution depth, and corresponding alteration intensity of the deep reservoir are determined by the well profile of the deep reservoir. The diagenetic sequence map is generated based on the diagenetic type, the type of syn-sedimentary alteration, the distribution depth, and the corresponding alteration intensity.

4. The prediction method according to claim 1, characterized in that, The steps for generating the karst landform zoning map include: The dissolution geomorphology zoning map is generated based on the sedimentary paleogeography and microgeography of the deep reservoir; the dissolution geomorphology zoning map is used to characterize the top surface of the key strata of the deep reservoir.

5. The prediction method according to claim 1, characterized in that, The steps for generating the planar distribution map of the fluid system include: The paleofluid system evolution process and current fluid system state of the deep reservoir are determined based on the current fluid characteristics and pressure system recovery simulation process in the deep reservoir. The fluid system planar distribution map is generated based on the ancient fluid system evolution process and the current fluid system state.

6. The prediction method according to any one of claims 1 to 5, characterized in that, After predicting the dominant regions of the deep reservoir based on the reservoir sedimentary facies map, the reservoir diagenetic facies map, the dominant sedimentary facies, and the dominant diagenetic facies, the method further includes: Collect the first well logging evaluation parameters and the first seismic attribute parameters corresponding to the advantageous area; The second logging evaluation parameters and the second seismic attribute parameters of the tested wells are compared with the first logging evaluation parameters and the first seismic attribute parameters, respectively, to conduct well location verification for the advantageous area.

7. A device for predicting the dominant region of a deep reservoir, characterized in that, include: The reservoir sedimentary facies diagram determination module is used to determine the reservoir sedimentary facies diagram of the deep reservoir by means of the sedimentary structure and sedimentary facies of multiple single-well reservoirs, under the constraints of a pre-generated sedimentary-tectonic pattern diagram of the deep reservoir; wherein, the sedimentary facies is the part of the overlap of the early high-quality facies zone and the quasi-syngenetic diagenetic facies zone of the deep reservoir. The reservoir diagenetic facies diagram determination module is used to determine the reservoir diagenetic facies diagram of the deep reservoir based on the pre-generated diagenetic sequence diagram, dissolution geomorphology zoning diagram, and fluid system planar distribution diagram of the deep reservoir. The dominant facies determination module is used to determine the dominant sedimentary facies and dominant diagenetic facies of the deep reservoir based on the reservoir characteristics of drilling data and / or well profiles. The dominant region prediction module is used to predict the dominant regions of the deep reservoir based on the reservoir sedimentary facies map, the reservoir diagenetic facies map, the dominant sedimentary facies, and the dominant diagenetic facies.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method for predicting the dominant region of a deep reservoir according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method for predicting the dominant region of a deep reservoir as described in any one of claims 1 to 6.

10. A computer program product comprising a computer program / instructions, characterized in that, When executed by a processor, the computer program implements the steps of the method for predicting the dominant region of a deep reservoir as described in any one of claims 1 to 6.

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