A three-dimensional modeling method for reservoir configuration

Abstract

The present invention discloses a three-dimensional reservoir configuration modeling method, which relates to the field of reservoir configuration technology. The method includes establishing a basic database, identifying and dividing configuration units, identifying and characterizing single sand bodies, evaluating reservoir connectivity quality, and modeling reservoir configuration. The method comprehensively applies the research results of sequence stratigraphy, sand body planar distribution patterns, sand body superposition and interlayer patterns, sand body scale, and reservoir physical properties to establish three-dimensional structural models, phase models, and reservoir attribute models for different types of reservoirs. The established three-dimensional geological model can reflect the sedimentary characteristics of different reservoirs and the distribution characteristics and variation patterns of reservoir attributes in three-dimensional space. It can also explain the sedimentary genesis mechanism of reservoirs of different sedimentary system types, providing a scientific and reasonable geological model for the subsequent prediction of remaining oil distribution.

Description

Technical Field

[0001] The present invention relates to the technical field of reservoir configuration, and in particular to a three-dimensional modeling method for reservoir configuration. Background Art

[0002] The architectural unit is an important component of the reservoir and is also the key content of reservoir research through architectural means. It is generally believed that the architecture is a lithofacies collection with a certain geometric shape, lithofacies combination relationship and scale.

[0003] Reservoir architecture refers to the study of the geometry, size, location, extension, and stacking relationships of multiple hierarchical building blocks within a reservoir, as well as impermeable interlayers. This approach primarily originates from outcrop sedimentary studies and, compared to sedimentary facies research, features a finer scale and more distinct layers. Specifically, the stratigraphic layer is divided into a series of hierarchical reservoir building blocks controlled by different interfaces. This allows for the division and in-depth study of subsurface reservoir units, resulting in a more systematic and complete understanding of the reservoir's sedimentary development history.

[0004] In the later stages of oilfield development, the varying permeability of barriers within the reservoir significantly influences the flow of oil and water, particularly the formation and distribution of residual oil. Therefore, conducting detailed research on the architecture of underground reservoirs not only deepens our understanding of reservoir geology, but also unlocks the potential for residual oil development within sandstones, ultimately contributing to increased oil and gas recovery.

[0005] The concept of flow unit was proposed by CL Hean et al. in 1984. Due to the influence of sedimentation and burial diagenesis, the physical properties of each facies belt vary significantly. This means that different parts of the same facies belt have different "reservoir qualities," and thus their control over production dynamics varies. Therefore, they proposed dividing the Shannon sandstone into five "flow units," defining flow units as laterally and vertically continuous reservoir zones with similar permeability, porosity, and bedding characteristics. The identification of flow units depends not only on their geological characteristics and position within the vertical sequence, but also on their petrophysical properties, particularly porosity and permeability. The flow unit concept provides a quantitative definition for the division and mapping of sandstone reservoirs and a scientific basis for numerical simulations of reservoir dynamics.

[0006] Foreign countries have entered the quantitative stage from the qualitative stage in the division of flow units, which closely combines the concept of flow units with the concept of reservoir engineering, making it more conducive to application.

[0007] At present, there are two main aspects of work done on flow units in oilfield development geology: on the one hand, it is mainly to study the distribution law of interlayers in thick oil layers, and use stable or relatively stable interlayers to further subdivide the thick layers into multiple relatively independent oil-water movement units. This work was carried out earlier and more deeply in China. For example, during the "Eighth Five-Year Plan" period, in Shuanghe Oilfield, in order to cooperate with the secondary infill adjustment of the well network and the subsequent potential tapping work in the thick oil layers, the intra-layer interlayers and architectural structures of the thick oil layers were studied and applied to production; the second aspect: it is mainly the subdivision of sedimentary microfacies and architectural structure research. This work has been carried out to varying degrees in oilfields across the country, especially Daqing Oilfield has made great progress in the subdivision of sedimentary microfacies research. They regard each microfacies as a flow unit and apply it to the prediction of remaining oil-enriched areas in the secondary and tertiary infill work, with remarkable results.

[0008] Currently, numerous scholars at home and abroad have conducted extensive research on architectural units in onshore field outcrops and modern sediments. Combining qualitative and quantitative analysis methods, particularly for fluvial sedimentary architecture, a relatively comprehensive approach has been developed, laying the foundation for establishing a relevant knowledge base. However, current geological analysis and research on subsurface architecture is still insufficient, and quantitative characterization is still insufficient. In addition, methods for integrating reservoir architecture with three-dimensional geological modeling are also incomplete. Currently, many domestic scholars are gradually conducting research on architectural and modeling methods for fans and rivers, and have pointed out a process for three-dimensional architectural modeling based on deterministic means. This is of great significance for future research breakthroughs in this direction. To this end, we propose a three-dimensional reservoir architecture modeling method. Summary of the Invention

[0009] The purpose of the present invention is to solve the problems that the current geological analysis and research on underground configurations are still insufficient, the quantitative characterization is still insufficient, and the method of how to combine reservoir configurations for three-dimensional geological modeling is also not perfect. The present invention provides a three-dimensional modeling method for reservoir configurations.

[0010] In order to achieve the above-mentioned purpose, the present invention specifically adopts the following technical solutions:

[0011] A three-dimensional reservoir configuration modeling method includes the following steps:

[0012] Step 1: Establish a basic database, collect information, organize and classify it, and establish a basic database;

[0013] Step 2: Identification and division of structural units: Through core characterization and the establishment of sedimentary microfacies configuration, the distribution characteristics of the main layer of sedimentary microfacies are carefully described, the structural hierarchy is divided, and the types and characteristics of microfacies structural units are clarified;

[0014] Step 3: Identify and characterize single sand bodies, establish a composite sand body architecture model, and achieve detailed dissection of single sand bodies through model guidance, dynamic and static integration, vertical staging, and lateral demarcation. This will clarify the relationship between sand body distribution control factors and lateral cutting, and enable single sand body prediction.

[0015] Step 4: Reservoir connectivity quality evaluation: Based on the detailed characterization of single sand bodies, reservoir connectivity quality evaluation standards are established in combination with core well analysis and testing and secondary interpretation of well logging porosity and permeability data to finely characterize the inter-well reservoir quality connectivity relationship;

[0016] Step 5: Reservoir configuration modeling: Based on high-precision three-dimensional geological modeling, a main single sand body reservoir configuration model is established to achieve detailed characterization of the reservoir configuration and guide the preparation of development adjustment plans.

[0017] Furthermore, the identification and division of configuration units in step 2 includes core analysis and lithofacies division, establishment of logging phase template, single well phase analysis, well-connected profile phase and planar sedimentary microfacies analysis, and division and identification of configuration units.

[0018] Furthermore, the analysis of sedimentary facies distribution patterns includes the following steps:

[0019] A1. Sedimentation model study: Based on previous research results, we collected the latest field data, including well logging, well logging data, core and analytical data, completed standardized data processing of well logging curves, analyzed the sedimentary background of the work area, compared it with previous research results, and then preliminarily determined the sedimentary model of the study area;

[0020] A2. Lithologic Characteristic Study: All cored wells in the study area were lithologically named, with strata classified as conglomerate and gravelly sandstone, coarse sandstone, medium sandstone, fine sandstone, siltstone, and mudstone. The lithologic and electrical properties were meticulously characterized, and the rock-electrical relationship patterns of the work area were derived and applied to the lithologic classification of non-cored wells. Based on the characteristics of the sedimentary microfacies plan, inter-well lithologic comparisons were conducted to screen out favorable sand bodies and characterize their planar distribution characteristics.

[0021] A3. Well logging data analysis: Analyze, compile and organize the well logging interpretation data of all wells in the study area, draw sedimentary microfacies plan and cross-section maps, reservoir cross-section maps, and draw contour maps of sand body thickness, effective sand body thickness, porosity and permeability for each layer;

[0022] A4. Research on the connectivity of reservoir sand bodies in the work area. Based on the sedimentary characteristics analysis of the study area, a comparative analysis was conducted with previous research results on low-permeability reservoirs. Dynamic development data was used to analyze the connectivity between sand bodies.

[0023] A5. Well logging phase analysis: Based on the geophysical characteristics of the rock, the amplitude and morphology of the applied logging curve, the sedimentary phase analysis of the entire well section is carried out.

[0024] Furthermore, the configuration units are divided and identified, and a reservoir configuration classification scheme for the study area is established. The reservoir configuration units are divided into levels 1 to 5, and the one-to-one correspondence between each level of configuration units and time units is clarified. The SP curve return rate of the configuration unit is used to realize the identification of the configuration.

[0025] Furthermore, the identification and characterization of single sand bodies in step three includes analysis of sand body distribution patterns, sand body superposition patterns, and characterization of single sand bodies.

[0026] Furthermore, when evaluating the reservoir connectivity quality in step 4, from the perspective of core analysis, different lithologies have different physical properties and different seepage characteristics, and different lithology interfaces have a good response on the three-porosity curve and a more obvious response on the RT-RI amplitude difference. Therefore, density, neutron, acoustic wave, and RT-RI curves are selected to analyze the vertical flow unit. On the basis of establishing the reservoir connectivity quality evaluation standard, the inter-well reservoir quality connectivity relationship is finely characterized.

[0027] Furthermore, when evaluating the reservoir connectivity quality in step 4, by comparing the correlation between RQI, FZI and mercury injection pore structure parameters, RQI is more representative of the reservoir pore structure than FZI, and can better reflect the reservoir pore throat structure and reservoir porosity and permeability characteristics.

[0028] Furthermore, when statistically analyzing the sedimentary microfacies types developed in different flow units, the RQI, Φz and FZI of each sample were calculated based on the physical property data. With RQI and Φz as variables, the DBSCAN cluster analysis was used to divide the samples into five categories. According to the statistics of the flow unit division results, from category 1 to category 5 units, the porosity gradually decreased, the permeability gradually decreased, and the reservoir seepage capacity gradually weakened.

[0029] Furthermore, the reservoir configuration modeling in step five specifically includes comprehensively applying the research results of the previous sequence stratigraphy, sand body plane distribution pattern, sand body superposition and interlayer pattern, sand body scale and reservoir physical property characteristics, and establishing a three-dimensional structural model, phase model and reservoir attribute model for different types of reservoirs.

[0030] The beneficial effects of the present invention are as follows:

[0031] 1. This invention comprehensively applies previous research findings on sequence stratigraphy, sandbody planar distribution patterns, sandbody stacking and interlayer patterns, sandbody scale, and reservoir physical properties to develop three-dimensional structural, facies, and reservoir attribute models for different reservoir types. The resulting three-dimensional geological models can reflect the sedimentary characteristics of different reservoirs and the distribution and variation of reservoir attributes in three-dimensional space. They can explain the depositional mechanisms of reservoirs of different sedimentary systems and provide a scientific and reasonable geological model for subsequent prediction of remaining oil distribution. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a flow chart of three-dimensional reservoir configuration modeling in the present invention;

[0033] Figure 2 It is the interface division of different levels of sand body configuration hierarchical modeling in the present invention;

[0034] Figure 3 It is a schematic diagram of the definition of the flow unit of the present invention;

[0035] Figure 4 is a diagram of a seepage barrier according to the present invention;

[0036] Figure 5 is the sedimentary phase diagram of the present invention;

[0037] Figure 6 It is the DBSCAN flow chart of the present invention;

[0038] Figure 7 This is a reservoir flow unit division chart of the present invention;

[0039] Figure 8 It is a histogram of the proportion of sedimentary microfacies developed in each flow unit of the present invention. DETAILED DESCRIPTION

[0040] To make the objectives, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0041] See also Figure 1 The present invention provides a three-dimensional reservoir configuration modeling method, comprising the following steps:

[0042] Step 1: Establish a basic database, collect information, organize and classify it, and establish a basic database;

[0043] Step 2: Identification and division of structural units: Through core characterization and the establishment of sedimentary microfacies configuration, the distribution characteristics of the main layer of sedimentary microfacies are carefully described, the structural hierarchy is divided, and the types and characteristics of microfacies structural units are clarified;

[0044] Step 3: Identify and characterize single sand bodies, establish a composite sand body architecture model, and achieve detailed dissection of single sand bodies through model guidance, dynamic and static integration, vertical staging, and lateral demarcation. This will clarify the relationship between sand body distribution control factors and lateral cutting, and enable single sand body prediction.

[0045] Step 4: Reservoir connectivity quality evaluation: Based on the detailed characterization of single sand bodies, reservoir connectivity quality evaluation standards are established in combination with core well analysis and testing and secondary interpretation of well logging porosity and permeability data to finely characterize the inter-well reservoir quality connectivity relationship;

[0046] Step 5: Reservoir configuration modeling: Based on high-precision three-dimensional geological modeling, a main single sand body reservoir configuration model is established to achieve detailed characterization of the reservoir configuration and guide the preparation of development adjustment plans.

[0047] In this embodiment, preferably, the identification and division of configuration units in step 2 includes core analysis and lithofacies division, establishment of logging phase template, single well phase analysis, well-connected profile phase and planar sedimentary microfacies analysis, and division and identification of configuration units.

[0048] Core analysis and lithofacies classification refer to the classification of sedimentary facies based on lithology, grain size, sedimentary structure and color. The grain size distribution characteristics can directly reflect the hydrodynamic conditions and energy when the sediments were formed. It is an important physical sign for judging the sedimentary environment and analyzing the hydrodynamic conditions. Coarse-grained sandstone with coarse grain size has good compressive resistance and relatively good physical properties. However, inequigranular sandstone and conglomerate often have poor physical properties due to poor sorting or high mud matrix content. Fine-grained sandstone often has poor physical properties due to poor compressive resistance and high mud content.

[0049] Sedimentary structures are structural phenomena formed by physical, chemical, and biological processes during or after sedimentation. Structures formed during sedimentation are called primary structures, such as flow-induced structures. Structures formed after sedimentation include syngenetic deformation structures formed before sediments consolidated into rock, and chemical structures formed after sediments consolidated into rock. Sedimentary structures are important indicators for analyzing and determining sedimentary environments, such as the sedimentary medium and energy levels.

[0050] Sedimentary structures include the following categories:

[0051] (1) Parallel bedding: This is composed of laminar sands and silts that are parallel to each other and to the bedding planes. It is typically well-developed in fine and medium sands. The bedding surfaces exhibit detachment lineations, where the long grain faces are parallel to the direction of water flow, indicating the direction of paleocurrents. Parallel bedding occurs in rapids and high-energy environments, under conditions of strong hydrodynamic forces, rather than as a product of static water deposition.

[0052] (2) Massive bedding: Also known as homogeneous bedding, this is a type of bedding that presents a roughly homogeneous appearance and does not have any laminar structure. Because the internal material is relatively uniform, there is no obvious difference in composition and structure, so the bedding does not show fine layer structure. Massive bedding is developed in both fine-grained and coarse-grained sediments. It can be either a very rapid deposition of suspended matter or a very dense, unsorted sediment deposition. At its bottom, scour surfaces are often seen, which contain mud and gravel of different colors and sizes. They often show a scour contact relationship with the underlying rock layer with a sudden change in lithology. This reflects the period of underwater distributary channel deposition when the water dynamics were strong and abrupt, and the sediment supply was relatively sufficient.

[0053] (3) Trough cross-bedding: The bottom boundary of the stratum is a trough-shaped scour surface, and the laminae are cut at the top. In the cross-section perpendicular to the flow direction, the foreset laminae and the lower interface appear trough-shaped, and the two are roughly parallel to each other or intersecting, and always intersecting with the upper interface. The shape of the groove can be symmetrical or asymmetrical, and the inclination of its long axis is consistent with the flow direction. In the cross-section parallel to the flow direction, the upper and lower interfaces are both gently curved downward, converging and intersecting at one or both ends; the foreset laminae have the same inclination and intersect with the interface obliquely.

[0054] (4) Cross-bedding: Cross-bedding is also commonly called oblique bedding. It is formed by the flow of a sedimentary medium with a certain flow rate, which produces sand waves moving downstream, forming a series of laminae that are oblique to the interface of the layer system. These oblique layers can be combined with each other in an overlapping and staggered manner. The cross-bedding seen in the study area is mainly sand ripple cross-bedding, which mainly appears in siltstone. It is a small-scale cross-bedding with low angles in multiple layers. The interface of the layer system is straight with the laminae, intersecting at a low angle in a wedge shape. The grain size within the laminae is well sorted, and there may be changes in grain order. The lower boundary of the layer system is a micro-wave shape, and the fine layers are inclined to one side and converge downward. It is formed by the migration of sand ripples and is a product of a sedimentary environment with weak energy conditions in the sedimentary medium.

[0055] (5) Scour surface: The core usually shows a curved, concave lithologic abrupt change. The grain size above the scour surface is usually coarser than that below it, accompanied by coarse-grained retained sediments such as gravel or mud gravel. The appearance of scour surface and retained sediments reflects high hydrodynamic energy, strong transport capacity, and downcutting erosion, and is often found at the bottom of the river channel.

[0056] (6) Imbricate structure: This refers to the phenomenon in which flat gravels are arranged in the same direction under the action of flowing water. The most common relationship between the imbrication of gravels and the direction of the water flow is upstream imbrication, that is, the inclination direction of the largest flat surface of the gravel is opposite to the direction of the water flow. The reason for this arrangement is that the force exerted by the water flow on the tile-like particles is a pulling force. The direction of this force is opposite to the hydraulic lifting force, which presses the particles to the bottom of the water. Therefore, the imbricate sedimentary structure is formed.

[0057] Well logging facies templates were established. Well logging facies analysis is primarily based on data provided by natural gamma ray and spontaneous potential curves, combined with acoustic transit time, density, neutron, deep induction, and deep lateral curves. Based on their shape, amplitude, top-bottom contact, and smoothness, a comprehensive analysis of sedimentary characteristics such as lithologic variations, grain size trends, sorting, heterogeneity, mud content, and rhythmicity is conducted. These characteristics reflect environmental characteristics such as the hydrodynamic conditions of the sedimentary medium, the supply of material, and changes in sedimentation rates during sediment deposition. Different facies belt types exhibit different logging responses on electrical logging curves, influenced by lithology, sedimentary environment, and development location. The amplitude, shape, contact, and smoothness of the logging curves can, to a certain extent, reflect the hydrodynamic conditions and sedimentation rate changes and characteristics during sediment deposition.

[0058] The electrical characteristics of the logging curve can well reflect the sedimentary characteristics of the formation. Through lithologic logging data and core analysis data, we can establish a match between the typical logging curve characteristics and their corresponding sedimentary environment to form logging phase markers. For example, a typical coal seam section represents shallow swamp environment deposition, and the logging curve characteristics are extremely low gamma (lower than the sandstone section), (wellbore is generally prone to collapse), extremely high resistivity (higher than sandstone), high acoustic wave, high neutron, and low density; the logging curve of a large and thick coal seam is box-shaped, and the coal line often appears as a spike; the logging curve characteristics of a typical sandstone section are low gamma, generally no wellbore collapse, high resistivity (higher than mudstone), low acoustic wave, low neutron, and high density. According to the genesis of the sand body, that is, the sedimentary environment of the sand body, the diversion channel sand and the estuary bar sand will have different responses and show different characteristics on the logging curve. The logging curve of the positive cycle channel sand is bell-shaped, and the estuary bar sand of the reverse cycle will be funnel-shaped; the logging curve characteristics of a typical mudstone section are high gamma, generally serious wellbore collapse, low resistivity, low acoustic wave, high neutron, and low density, and the logging curve is generally box-shaped.

[0059] The specific forms of logging curve combination characteristics can characterize specific sedimentary products and sedimentary environments. The logging curve combination characteristics formed by common lithologies and sedimentary environments are easy to identify. According to the observation and comparison of the entire area, the main types of logging curve combination characteristics of the Lower Jurassic sedimentary reservoirs in the work area are: box curve, funnel curve, bell curve, finger curve, single peak curve, and sawtooth curve.

[0060] Box curves: This type of curve has a wide longitudinal width, with consistently low GR values ​​and consistently high RD values, intermittently jagged in between. However, the overall scale value fluctuates little, and the box-like appearance reveals abrupt contact with both the overlying and underlying strata. This type of curve reflects rapid, thick sedimentation over a short period of time, characterized by high and stable water energy, relatively uniform sediment grain size, and good sorting. This curve characteristic is found in large, thick sections of sandstone deposits in the target strata of the study area, indicating distributary channel deposition or the superposition of multiple sand bodies.

[0061] Bell-shaped curves: This type of curve has a narrow top and a large bottom. Specifically, the closer to the top, the larger the GR value and the smaller the RD value; the closer to the bottom, the smaller the GR value and the larger the RD value. This bell-shaped curve has a gradual contact with the overlying strata and a sudden contact with the underlying strata, reflecting the gradual weakening of the energy of the sedimentary water. Sediment grain size shows a positive sequence from coarse to fine from bottom to top, indicating a depositional origin of retrogradation or channel migration. Single-stage channel sediment sand bodies in the target strata in the study area often exhibit this logging characteristic.

[0062] Funnel-shaped curves: This type of curve has a wide amplitude at the top and a narrow amplitude at the bottom. That is, the closer to the top, the smaller the GR value and the larger the RD value; the closer to the bottom, the larger the GR value and the smaller the RD value. Its shape resembles a funnel, with abrupt contact with the overlying strata and gradual contact with the underlying strata, reflecting the gradual increase in the energy of the sedimentary water. Sediment grain size exhibits an inverse sequence from fine to coarse from bottom to top, indicating a depositional origin of progradation or downstream aggradation. This logging characteristic is common in the single-stage normal delta front subfacies river mouth bar sedimentary sand bodies of the target strata in the study area.

[0063] Finger-like curve: This type of curve combination has a narrow vertical development range, with the GR value suddenly changing from a high value to a low value, and the RD value suddenly changing from a low value to a high value. It looks like a finger and shows a sudden contact with the overlying and underlying strata, reflecting a sudden change in the grain size of adjacent sediments caused by a significant change in the energy of the sedimentary water or a sudden interruption in the sediment supply. The coarse-grained sediments and the fine-grained sediments are interdeveloped, representing the deposition of thin sand bodies. The sheet sand at the delta front and the beach-bar sand deposits of the shallow lake in the target layer of the study area have this characteristic curve combination.

[0064] Single-peak curves: These curves are characterized by a sudden appearance of high amplitude within a long, stable, low-amplitude logging curve, and appear to have a spike-like shape. The vertical width of the spike is narrow, and it exhibits abrupt contact with the overlying and underlying strata. This indicates a significant change in the energy of the sedimentary water, from a long-term low-energy environment to a high-energy one. This typically reflects depositional events such as floods, or a sudden recovery in sediment supply, resulting in a significantly coarser grain size than the adjacent overlying and underlying strata.

[0065] Sawtooth curves: This type of log curve in the study area is typically an evolution of other types of curves. Based on box, funnel, and bell curves, the log curve undergoes a linear shift within the stable curve development zone, fluctuating and extending, presenting a sawtooth appearance. This primarily reflects the frequent and persistent occurrence of low-energy depositional environments. Sand bodies deposited in the normal delta front underwater distributary channels of the target formation in the study area often exhibit this type of log response, indicating that during sand body deposition, reduced water energy led to the incorporation of fine-grained sediments into the channel sandstone, causing the log curve to regress.

[0066] Single-well facies analysis is an essential step in identifying microfacies. Single-well facies analysis involves meticulous observation, description, analysis, and identification of cores from cored wells. This analysis provides various facies information (such as lithology and lithologic combinations, primary sedimentary structures and structures, biofossil characteristics, grain size analysis results, and facies sequence characteristics). This comprehensive analysis then generates a single-well facies analysis histogram. The single-well facies analysis histogram primarily reflects the facies signatures of sand layers, determining facies types and vertical facies sequences, as well as selected facies logging curves. Using established models for the relationship between lithofacies and logging facies, logging facies can be used to directly identify reservoir sedimentary microfacies. The configuration of facies sequences can effectively reflect the evolutionary development of sedimentary facies belts throughout geological history. The vertical stacking of different facies belts intuitively reflects the evolution of the sedimentary environment at a single well point and is a direct product of the sedimentary hydrodynamic environment.

[0067] In this embodiment, preferably, the sedimentary facies distribution law is analyzed. On the basis of systematic phase marker research and unified stratification of single well profiles, the sedimentary microfacies types of each layer are divided, and then the logging curve characteristics corresponding to different sedimentary microfacies in the cored well section are further studied. Based on seismic, logging, core and outcrop data, the logging curve response characteristics and profile combinations unique to each type of sedimentary microfacies are determined in the isochronous stratigraphic grid, and the conversion relationship between logging phases and sedimentary phases is established; on the basis of the single well sedimentary microfacies research, the vertical sedimentary sequence sequence and the planar distribution law of sedimentary microfacies are finally determined through different connected well profiles.

[0068] (1) Sedimentation model research

[0069] Based on the research results of predecessors, the latest field data were collected, including mud logging, well logging data, core and analytical test data, and standardized data processing of logging curves was completed. The sedimentary background of the work area was analyzed and compared with the research results of predecessors, and then a preliminary judgment was made on the sedimentary pattern of the study area.

[0070] (2) Study on lithologic characteristics

[0071] Lithologic naming was performed on all cored wells in the study area, with strata classified as conglomerate and gravelly sandstone, coarse sandstone, medium sandstone, fine sandstone, siltstone, and mudstone. The lithologic and electrical properties were meticulously characterized, resulting in a detailed rock-electrical relationship within the study area and applied to the lithologic classification of non-cored wells. Based on the characteristics of the sedimentary microfacies plan, inter-well lithologic comparisons were conducted to identify favorable sand bodies and characterize their planar distribution.

[0072] (3) Well logging data analysis

[0073] The logging interpretation data of all well locations in the study area were analyzed, counted and sorted out, and sedimentary microfacies plan and cross-sectional maps, reservoir cross-sectional maps were drawn. Contour maps of sand body thickness, effective sand body thickness, porosity and permeability were drawn for each small layer.

[0074] (4) Research on the connectivity of reservoir sand bodies in the work area

[0075] Based on the analysis of the sedimentary characteristics of the study area, a comparative analysis was conducted with previous research results on low-permeability reservoirs. Dynamic development data was used to analyze the connectivity between sand bodies.

[0076] (5) Well logging phase analysis

[0077] Well logging facies analysis is a method for analyzing sedimentary facies throughout a wellbore interval based on the geophysical characteristics of rocks and the amplitude and morphology of well logging curves. It effectively compensates for the inadequacy of core data. Well logging facies reflects the balance between provenance and water flow energy during sediment deposition. Facies classification of well logging curves allows reconstruction of sedimentary formations characterized by provenance, water flow energy, mud content, sedimentary rhythms, and even paleogeomorphological features during deposition.

[0078] See also Figure 2 In this embodiment, preferably, the configuration units are divided to establish a reservoir configuration classification scheme for the study area, and the one-to-one correspondence between each level of configuration units and time units is clarified.

[0079] The level 5 interface is the top and bottom interface of a short-term cycle, equivalent to a small layer, representing the beginning and end of the development of a delta front lobe. It is a complex of multiple genetic sand bodies with a thickness of more than ten to several meters. The sand body extends over a large range, ranging from several kilometers to several hundred meters. The level 5 interface mainly exists in mudstone interlayers of a certain scale, and its local distribution is stable within the oil field.

[0080] Level 4 interfaces represent the top and bottom interfaces of ultra-short-term cycles, equivalent to a single genetic sand body. These interfaces are defined by the top and bottom interfaces of the genetic sand body, which can be several meters thick and extend laterally from hundreds to tens of meters. Each genetic sand body (especially underwater distributary channels) significantly incises the underlying strata, remaining connected to the underlying strata or retaining only a very thin interlayer of physical properties at the top. These interfaces serve as markers for the demarcation and comparison of genetic sand bodies, have a defined distribution range, and can be tracked between wells.

[0081] The third-level interface is a sedimentary discontinuity or scour surface between sand layers in the genetic sand body, and is often accompanied by thin mud interlayers above and below the interface.

[0082] Level 1 and 2 structural interfaces have less pronounced logging response characteristics, have little impact on remaining oil distribution, and can only be identified in core data. Therefore, they are not the subject of this chapter's study. This chapter focuses on the 3rd, 4th, and 5th structural units of the sand bodies. First, potential structural interfaces are identified using logging and core data. A 5th-level structural study is then conducted throughout the entire area, followed by a 4th-level structural study. Building on this 4th-level structural study, the 3rd-level structural units are further identified and divided, ultimately establishing qualitative and quantitative models of the structural units within the oil-bearing formations in the study area.

[0083] In identifying architectural units, Level 5 interfaces are interlayers between mouth-bar complexes, with high SP curve reversions. Level 5 interfaces in the study area are extensive, thick, and extensive prodeltaic mud layers with stable distribution. They are the highest-level sedimentary interface identifiable within the delta-front sedimentary bodies in the study area. They are impermeable and constitute a well-defined interlayer. Level 4 interfaces are interlayers between single mouth-bars, with significant SP curve reversions. Level 4 interfaces in the study area are composed of mudstone or silty mudstone, are thick, have relatively stable planar development, and extend over a wide range. They demarcate rhythmic layers within the delta-front mouth-bar deposits in the study area and serve as the primary seepage barrier within the sublayer. Level 5 and Level 4 architectural interfaces are generally widespread, with distinct interlayers above them, making them easy to identify and providing strong interwell comparison. Therefore, deterministic modeling is often used to 3D model Level 5 and Level 4 architectural interfaces in the study area. Since the development range of the Level 3 interface is limited and the identification characteristics are weak, in areas with less data, it is often necessary to conduct inter-well prediction based on the identification of interlayers at the Level 3 interface and the typical dynamic data of the study area to determine the interlayer development pattern and angle development range in the study area, obtain inter-well interlayer prediction results with a high degree of credibility, and use this to control the hierarchical modeling of the Level 3 interface in the study area.

[0084] In this embodiment, the identification and characterization of single sand bodies in step three preferably includes analysis of sand body distribution patterns, sand body superposition patterns, and single sand body characterization. Due to the rise and fall of the sedimentary base level, the hydrodynamics of different sedimentary areas in the study area vary in strength, resulting in different vertical superposition relationships of sand bodies deposited at different times and locations. This paper, through the dissection of the established horizontal and vertical well sections, found that there are three single sand body superposition patterns in the study area: separated, superimposed, and cut-and-stacked.

[0085] Single sand bodies are separated. This separation pattern is widespread in the study area and may evolve into a superimposed pattern toward the provenance. This separation pattern manifests itself in cross-section as two single sand bodies separated by muddy, physical, or calcareous interlayers. The relatively complete preservation of interlayers between sand bodies is primarily due to the fact that the depositional area is located far from the provenance or depocenter, where hydrodynamic forces are weak and lake waves and currents have little influence on the erosion of previously deposited fine-grained sediments.

[0086] Single sandbody superposition. This superimposed pattern generally occurs in the main body of the sandbody near the provenance, gradually becoming separated toward the sandbody edge. Due to the strong hydrodynamics near the provenance, the thickness of fine-grained sediments between the two sandbodies is small and the development range is limited, so the two sandbodies often appear in direct contact and superimposed production.

[0087] Single sand body incision and stacking patterns occur in areas with developed underwater distributary channels. These patterns often manifest as previously deposited mouth bars being cut by underwater distributary channels, resulting in a reduction in the thickness of the mouth bars. These patterns are prevalent upstream of underwater distributary channels, where hydrodynamic forces are strong. As the underwater distributary channels extend forward, the channel's incision gradually weakens, and the incision and stacking patterns are gradually replaced by superimposed or separated patterns.

[0088] In this embodiment, preferably, the specific method of evaluating the reservoir connectivity quality in step 4 is to select density, neutron, acoustic wave, and (RT-RI) curves to analyze the vertical flow unit, and on the basis of establishing the reservoir connectivity quality evaluation standard, finely characterize the inter-well reservoir quality connectivity relationship.

[0089] See also Figure 3 Flow units, also known as rock physical flow units, reservoir flow units, and hydrodynamic flow units, are vertically and laterally continuous reservoir rock masses with similar rock physical properties that affect fluid flow. Flow unit classification is the core of flow unit research. Differences in seepage within interconnected bodies are caused by differences in reservoir quality. Identifying seepage differences is actually a truncation classification of relatively continuous seepage capacity. Core analysis shows that different lithologies have different physical properties and different seepage characteristics. Different lithologic interfaces have a good response on the three-porosity curve and a more obvious response in the RT-RI amplitude difference. Therefore, we choose density, neutron, acoustic wave, and RT-RI curves to analyze vertical flow units.

[0090] In this embodiment, the flow band index division method is preferably used among many flow unit division methods because of its quantitative identification and division characteristics, and is therefore widely used. The Kozeny-Karman porosity-permeability relationship is its theoretical basis. The specific formula is:

[0091] lg RQI=lgφ z +lg FZI

[0092] RQI stands for Reservoir Quality Index; Φz stands for Normalized Porosity Index; and FZI stands for Flow Zone Index, a parameter that integrates rock mineralogy, pore throat characteristics, and structural characteristics. The better the reservoir properties, the larger the FZI value. Identical FZI values ​​indicate similar reservoir properties and belong to the same flow unit.

[0093] The pore-throat geometry method classifies reservoir types from the perspective of rock fabric. The pore-throat radius when the mercury injection saturation on the mercury injection curve equals 35% reflects the fluid flow and development dynamics in the rock. Generally, the R35 value can be directly obtained from the mercury injection curve; if there is no mercury injection curve, the R35 value can be calculated using the Winland equation based on the core physical property analysis and the interpretation results of reservoir parameters from well logging curves. The specific formula is:

[0094] logR35 = 0.372 + 0.588lg(k) - 0.684lg(φ)

[0095] Each type of flow unit divided by the pore-throat geometry method has a unified pore-throat size distribution and similar reservoir properties. The better the pore-throat characteristics of the reservoir, the larger its R35 value. The pore-throat geometry method divides the reservoir into 5 types of flow units, namely, extremely coarse pore-throat type (R35 > 10μm), coarse pore-throat type (2μm < R35 < 10μm), medium pore-throat type (0.5μm < R35 < 2μm), fine pore-throat type (0.1μm < R35 < 0.5μm), and extremely fine pore-throat type (R35 < 0.1μm).

[0096] The Topsis method is a method for ranking according to the degree of proximity of a finite number of evaluation objects to the ideal target, and it evaluates the relative advantages and disadvantages of existing objects. Its basic principle is to rank by detecting the distances between the evaluation objects and the positive ideal solution and the negative ideal solution. If an evaluation object is closest to the positive ideal solution and farthest from the negative ideal solution at the same time, it is the best. The Topsis method includes 5 steps: constructing a normalized initial matrix for the evaluation parameters, determining the weights, determining the decision matrix, determining the positive ideal solution and the negative ideal solution, and determining the degree of closeness.

[0097] Construct a normalized initial matrix. Assume there are m samples to be evaluated, and each object has n indicators. Then the original data matrix X is:

[0098]

[0099] In the formula: m is the number of samples to be evaluated; n is the number of indicators; x ij is the value of the j-th indicator of the i-th sample.

[0100] Since the unit dimensions of different evaluation indicators are not the same, resulting in relatively large differences in the absolute numerical values of indicators such as porosity and permeability, it is necessary to normalize the evaluation indicators first:

[0101]

[0102] After normalization, the initial matrix is obtained:

[0103]

[0104] Determine the weight of the evaluation index. The determination of the weight of the evaluation index is the key to the division of the flow unit, which directly determines the evaluation model and the division results. The study introduces the concept of "entropy" to objectively and quantitatively assign weights. Entropy reflects the uncertainty of information, that is, it measures the degree of uncertainty in a system. The larger the entropy, the more dispersed the distribution of the system or indicator, and the stronger its uncertainty; the smaller the entropy, the weaker its uncertainty. In weight analysis, if the entropy value of an evaluation index is larger, it means that the weight of the index is greater. According to the entropy value e j Definition:

[0105]

[0106] Calculate the index difference h j :

[0107]

[0108] Among the n indicators involved in the evaluation, the weight of the jth indicator is:

[0109]

[0110] Determine the decision matrix. The decision matrix V is the normalized index value multiplied by its corresponding weight value:

[0111]

[0112] Determine positive and negative ideal solutions. A positive ideal solution represents the most ideal value for each evaluation parameter, while a negative ideal solution represents the least ideal value. During the solution process, it is important to note the physical meaning of the evaluation parameter values ​​and the corresponding relationship between the positive and negative ideal solutions. For example, higher values ​​for benefit-oriented parameters such as porosity and permeability indicate better reservoir quality, while higher values ​​for cost-oriented parameters such as shale content indicate worse reservoir quality.

[0113]

[0114] Where: J1 is the benefit parameter; J2 is the cost parameter.

[0115] Determine the degree of closeness and calculate the distance between each evaluation object and the positive and negative ideal solutions. The closer the distance to the positive ideal solution, the closer the relative closeness, and the better the reservoir quality of the flow unit.

[0116] The distance between the sample and the positive ideal solution:

[0117]

[0118] The distance between the sample and the negative ideal solution:

[0119]

[0120] Relative closeness D i for:

[0121]

[0122] Where 0≤D i ≤1, D i The closer it is to 1, the better the evaluation object is.

[0123] Core analysis shows that different lithologies have different physical properties and seepage characteristics. Different lithology interfaces have good responses on the three-porosity curves and also have obvious responses on the RT-RI amplitude difference. Therefore, density, neutron, acoustic wave, and RT-RI curves are selected to analyze the vertical flow unit.

[0124] Reservoir quality index:

[0125]

[0126] Where, K is the reservoir permeability, Φ e —Effective porosity of the reservoir, decimal.

[0127] Ratio of pore volume to particle volume:

[0128]

[0129] Stratum flow zone index:

[0130] FZI=RQI / Φz

[0131] The distribution of flow units is controlled by parameters such as sedimentation, diagenesis, macroscopic rock properties, and microscopic pore structure. Therefore, when selecting reservoir flow unit demarcation parameters, comprehensive and appropriate principles should be followed, fully considering factors such as sedimentation, diagenesis, macroscopic and microscopic, and dynamic and static factors. Furthermore, the geological reservoir characteristics and the abundance of data in the study area should be considered to ensure that the selected parameters can objectively and truly reflect the reservoir's seepage capacity, are easily accessible in the study area, and have good replicability.

[0132] The distribution of flow units is closely related to the sedimentary environment, with mud content and median grain size being the most commonly used parameters to reflect the sedimentary environment. The reservoir's storage and seepage capacity play a decisive role in the division of flow units. Within the same sedimentary facies belt, vertical and lateral physical property differences are evident. Porosity and permeability are the most representative parameters, providing good physical property indicators and being easily accessible. Therefore, porosity and permeability are selected as parameters reflecting physical conditions for evaluation. In addition to the macroscopic sedimentary environment, diagenetic conditions, and physical properties, rock micropore structure is also an important factor influencing fluid migration. Pore throat radius, mercury withdrawal efficiency, and median saturation pressure are the most commonly used parameters to characterize rock micropore structure, which can directly reflect reservoir connectivity. There are few analytical data on pore throat radius, mercury removal efficiency and median saturation pressure in the study area. The pore throat radius and mercury removal efficiency have poor correlation with permeability and water absorption intensity of injection wells, while the median saturation pressure has a good correlation with permeability and water absorption intensity of injection wells, indicating that the median saturation pressure reflects the differences in the microscopic pore structure of the rock, which in turn affects the seepage capacity of the rock. Therefore, the median saturation pressure is selected as the parameter reflecting the microscopic pore structure of the rock to divide the flow unit.

[0133] By comparing the correlations between RQI, FZI and mercury injection pore structure parameters, it is found that RQI is more representative of reservoir pore structure than FZI and can better reflect the reservoir pore throat structure and reservoir porosity and permeability characteristics.

[0134] See also Figure 4-5 Reservoir connectivity parameter analysis divides reservoir seepage barriers into four levels, from large to small, based on the delta's reservoir architecture hierarchy. Flow units are divided based on secondary and tertiary seepage barriers. Secondary levels correspond to multiple sedimentary microfacies combinations, while tertiary levels correspond to single microfacies.

[0135] Based on the configuration division, the relationship between sand body superposition and interlayer distribution characteristics are identified. The reservoir with good sand body superposition, large thickness and low mud content has good connectivity; the more interlayers, the greater the mud content, and the poorer the connectivity.

[0136] According to reservoir connectivity parameter analysis, the RQI is more representative of reservoir pore structure than the FZI, and can better reflect the reservoir pore throat structure and reservoir porosity and permeability characteristics. Therefore, the use of the RQI to divide reservoir flow units is more advantageous.

[0137] In this embodiment, preferably, when statistically analyzing the sedimentary microfacies types developed in different flow units, the RQI, Φz, and FZI of each sample are calculated based on the physical property data. Using RQI and Φz as variables, DBSCAN cluster analysis is used to classify the samples into five categories.

[0138] See also Figure 6DBSCAN cluster analysis is an unsupervised ML clustering algorithm, standing for Density-Based Spatial Clustering of Noise Applications. The DBSCAN algorithm finds all dense regions of sample points and treats these dense regions as clusters. DBSCAN cluster analysis has three key features: 1. It uses density to filter out noise points far from the core density; 2. It does not require a known number of clusters; and 3. It can discover clusters of any shape.

[0139] See also Figure 7 According to the statistics of the flow unit division results, from type 1 unit to type 5 unit, the porosity gradually decreases, the permeability gradually decreases, and the reservoir seepage capacity gradually weakens.

[0140] Reservoir flow unit division standards and physical property characteristics statistics

[0141]

[0142] ① Difference in river channel elevation ② Difference in river channel scale ③ Lateral migration of river channel ④ Appearance of dam edge microfacies

[0143] ⑤ Differences in the size of estuary dams ⑥ Lateral overlap of estuary dams ⑦ Differences in the elevation of estuary dams

[0144] ⑧The river flows over the dam ⑨The dam is deposited on the river sand

[0145] A statistical analysis of the development of flow units in each sublayer shows that the reserves of type I flow units are the smallest, type III flow units have the largest reserves, and type IV flow units also have relatively large reserves.

[0146] Statistical table of the development of each flow unit in each sublayer

[0147]

[0148] Statistical table of reserves distribution of each flow unit

[0149]

[0150] Statistical table of the proportion of sedimentary microfacies developed in each flow unit

[0151]

[0152] See also Figure 8Statistical analysis of the sedimentary microfacies types developed in different flow units shows that the seepage capacity of the underwater distributary channel phase is the best, with type 3 flow units being the most developed, and the proportions of types 4 and 5 decreasing in turn; the seepage capacity of the remote sand bar phase is relatively poor, with the proportion increasing from type 2 to type 5, the seepage capacity of the sheet sand phase is the worst, with almost only type 5 flow units developed, and the seepage capacity of the estuary bar phase is between the underwater distributary channel and the remote sand bar phase, with types 3 and 5 being relatively developed, with no obvious pattern.

[0153] In this embodiment, preferably, the reservoir configuration modeling in step 5 specifically includes comprehensively applying the research results of the previous sequence stratigraphy, sand body planar distribution patterns, sand body superposition and interlayer patterns, sand body scale, and reservoir physical properties to establish a three-dimensional structural model, phase model, and reservoir attribute model for different types of reservoirs. The established three-dimensional geological model can reflect the sedimentary characteristics of different reservoirs and the distribution characteristics and variation patterns of reservoir attributes in three-dimensional space, and can explain the sedimentary genetic mechanism of reservoirs of different sedimentary system types, providing a scientific and reasonable geological model for the subsequent prediction of remaining oil distribution.

[0154] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A reservoir configuration three-dimensional modeling method, characterized in that: It includes the following steps: Step 1: Establish a basic database, collect information, organize and classify it, and establish a basic database; Step 2: Identification and division of structural units: Through core characterization and the establishment of sedimentary microfacies configuration, the distribution characteristics of the main layer of sedimentary microfacies are carefully described, the structural hierarchy is divided, and the types and characteristics of microfacies structural units are clarified; Step 3: Identify and characterize single sand bodies, establish a composite sand body architecture model, and achieve detailed dissection of single sand bodies through model guidance, dynamic and static integration, vertical staging, and lateral demarcation. This will clarify the relationship between sand body distribution control factors and lateral cutting, and enable single sand body prediction. Step 4: Reservoir connectivity quality evaluation: Based on the detailed characterization of single sand bodies, reservoir connectivity quality evaluation standards are established in combination with core well analysis and testing and secondary interpretation of well logging porosity and permeability data to finely characterize the inter-well reservoir quality connectivity relationship; Step 5: Reservoir configuration modeling: Based on high-precision three-dimensional geological modeling, a main single sand body reservoir configuration model is established to achieve detailed characterization of the reservoir configuration and guide the preparation of development adjustment plans.

2. A reservoir configuration three-dimensional modeling method according to claim 1, characterized in that: The identification and division of configuration units in step 2 include core analysis and lithofacies division, establishment of logging phase template, single well phase analysis, well-connected profile phase and planar sedimentary microfacies analysis, and division and identification of configuration units.

3. A reservoir configuration three-dimensional modeling method according to claim 1, characterized in that: The analysis of sedimentary facies distribution patterns includes the following steps: A1. Sedimentation model study: Based on previous research results, we collected the latest field data, including well logging, well logging data, core and analytical data, completed standardized data processing of well logging curves, analyzed the sedimentary background of the work area, compared it with previous research results, and then preliminarily determined the sedimentary model of the study area; A2. Lithologic Characteristic Study: All cored wells in the study area were lithologically named, with strata classified as conglomerate and gravelly sandstone, coarse sandstone, medium sandstone, fine sandstone, siltstone, and mudstone. The lithologic and electrical properties were meticulously characterized, and the rock-electrical relationship patterns of the work area were derived and applied to the lithologic classification of non-cored wells. Based on the characteristics of the sedimentary microfacies plan, inter-well lithologic comparisons were conducted to screen out favorable sand bodies and characterize their planar distribution characteristics. A3. Well logging data analysis: Analyze, compile and organize the well logging interpretation data of all wells in the study area, draw sedimentary microfacies plan and cross-section maps, reservoir cross-section maps, and draw contour maps of sand body thickness, effective sand body thickness, porosity and permeability for each layer; A4. Research on the connectivity of reservoir sand bodies in the work area. Based on the sedimentary characteristics analysis of the study area, a comparative analysis was conducted with previous research results on low-permeability reservoirs. Dynamic development data was used to analyze the connectivity between sand bodies. A5. Well logging phase analysis: Based on the geophysical characteristics of the rock, the amplitude and morphology of the applied logging curve, the sedimentary phase analysis of the entire well section is carried out.

4. A reservoir configuration three-dimensional modeling method according to claim 1, characterized in that: Division and identification of configuration units, establishment of a reservoir configuration classification scheme for the study area, dividing reservoir configuration units into levels 1 to 5, clarifying the one-to-one correspondence between configuration units at each level and time units, and using the SP curve return rate of the configuration unit to realize configuration identification.

5. The reservoir configuration three-dimensional modeling method according to claim 1, characterized in that: The identification and characterization of single sand bodies in step three includes analysis of sand body distribution patterns, sand body superposition patterns, and characterization of single sand bodies.

6. A reservoir configuration three-dimensional modeling method according to claim 1, characterized in that: When evaluating the reservoir connectivity quality in step 4, core analysis shows that different lithologies have different physical properties and different seepage characteristics, and different lithologic interfaces have a good response on the three-porosity curve and a relatively obvious response on the RT-RI amplitude difference. Therefore, density, neutron, acoustic wave, and RT-RI curves are selected to analyze the vertical flow unit. On the basis of establishing the reservoir connectivity quality evaluation standard, the inter-well reservoir quality connectivity relationship is finely characterized.

7. The reservoir configuration three-dimensional modeling method according to claim 1, characterized in that: When evaluating the reservoir connectivity quality in step 4, by comparing the correlation between RQI, FZI and mercury injection pore structure parameters, RQI is more representative of the reservoir pore structure than FZI, and can better reflect the reservoir pore throat structure and reservoir porosity and permeability characteristics.

8. The reservoir configuration three-dimensional modeling method according to claim 6, characterized in that: When statistically analyzing the sedimentary microfacies types developed in different flow units, the RQI, Φz and FZI of each sample were calculated based on the physical property data. With RQI and Φz as variables, the DBSCAN cluster analysis was used to divide the samples into five categories. According to the flow unit division results, the porosity and permeability gradually decreased from category 1 to category 5, and the reservoir seepage capacity gradually weakened.

9. The reservoir configuration three-dimensional modeling method according to claim 1, characterized in that: The reservoir configuration modeling in step five specifically includes comprehensively applying the research results of the previous sequence stratigraphy, sand body plane distribution pattern, sand body superposition and interlayer pattern, sand body scale and reservoir physical property characteristics, and establishing a three-dimensional structural model, phase model and reservoir attribute model for different types of reservoirs.

Images