Multi-stage river channel contact relation simulation method based on low-bending split-flow river channel deposition

Abstract

The invention relates to the technical field of low-permeability reservoir remaining oil description, in particular to a multi-stage river channel contact relation simulation method based on low-bending split-flow river channel deposition. The method comprises the steps that a target research area is determined, a single sand body level deposition unit is divided, and a single well logging facies mode is established; establishing an earthquake forward modeling model, and obtaining a well earthquake identification mode; recognizing the boundary of a single river channel according to the well-seismic recognition mode, and obtaining boundary points; combining the boundary points into a single riverway boundary of the cut and stacked sand body, and determining a sand body communication relation; according to a single river channel boundary identification result, firstly establishing a small-layer net gross ratio and permeability attribute model, and then establishing a multi-stage river channel constraint attribute model; and correcting the grid conductivity of the riverway boundary, establishing a multi-stage riverway contact relation simulation model, and depicting the type and part of the remaining oil in the target research area. According to the method provided by the invention, the historical fitting and remaining oil description precision of the low-permeability reservoir is improved, accurate description of remaining oil at different parts of the single sand body is realized, and targeted potential tapping is guided.

Description

Technical Field

[0001] This invention relates to the technical field of residual oil description in low-permeability reservoirs, and more particularly to a multi-stage channel contact relationship simulation method based on low-curvature distributary channel sedimentation. Background Technology

[0002] In practical applications, the description of remaining oil in low-permeability reservoirs mainly involves historical data fitting using geological modeling and numerical simulation software. Within an adjustable range, the accuracy of historical data fitting can be improved by modifying reservoir static parameters, oil-water property parameters, and production data. Reservoir static parameters include porosity and permeability, oil-water property parameters include PVT data and relative permeability data, and production data includes water injection volume, bottom hole flowing pressure, conductivity, and well index. When the fitting accuracy of the above main indicators is controlled within 5%, the statistically obtained remaining oil distribution becomes an important basis for subsequent targeted tapping of remaining oil potential.

[0003] Currently, low-permeability oil reservoirs often feature narrow sand bodies with multiple overlapping channel phases on a planar surface. The connectivity between oil and water wells on these channel sand bodies from different periods is complex, making it difficult for existing geological modeling and numerical simulation methods to describe the types of residual oil resulting from channel boundary obstruction, leading to low accuracy in residual oil description. Therefore, to address these shortcomings, a simulation method based on multi-phase channel contact relationships in low-torsional distributary channel sediments is proposed. Summary of the Invention

[0004] (a) Technical problems to be solved

[0005] This invention provides a multi-stage channel contact relationship simulation method based on low-bend distributary channel sedimentation, which overcomes the problem that existing conventional low-permeability reservoir geological modeling and numerical simulation methods have high historical fitting accuracy but low residual oil description accuracy.

[0006] (II) Technical Solution

[0007] To address the above problems, this invention provides a multi-stage channel contact relationship simulation method based on low-swerving distributary channel sedimentation, comprising:

[0008] Step 1: Determine the target study area, divide the target study area into multiple single sand body-level sedimentary units, and establish single-well logging facies models based on the closed core wells in each single sand body-level sedimentary unit;

[0009] Step 2: Establish a seismic forward model based on the various types of transverse overlapping of distributary channel sand bodies, and in conjunction with the single-well logging facies model, obtain the well-seismic identification modes corresponding to each type of transverse overlapping of distributary channel sand bodies;

[0010] Step 3: Based on the acquired multiple well seismic identification patterns, identify the boundaries of individual river channels well by well and row by row within the target study area, and obtain the boundary points of each individual river channel boundary.

[0011] Step 4: Based on the identified multiple boundary points, combine them into a single channel boundary of overlapping sand bodies, and determine the sand body connectivity of the single channel boundary of overlapping sand bodies;

[0012] Step 5: Based on the single channel boundary identification results, combined with well point data and seismic data of each single sand body-level sedimentary unit, establish a small-layer net-to-gross ratio and permeability attribute model using the single-stage channel facies constraint difference method;

[0013] Step 6: Obtain multi-phase channel facies maps within the target study area, determine channel boundaries based on these maps, and establish multi-phase channel constraint attribute models in conjunction with the net-to-gross ratio and permeability attribute models of the sublayer.

[0014] Step 7: Correct the grid conductivity of the river boundary based on the multi-phase river constraint attribute model, establish a multi-phase river contact relationship simulation model, and characterize the type and location of remaining oil in the target study area through the calculation results of the simulation model.

[0015] Preferably, in step one, the method for dividing the single sand body-level sedimentary units is based on the standard top and bottom layers and multi-stage floodplain reference layers in the target study area. First, the skeleton profile is closed and compared, and then the overall stratigraphic comparison is performed in the entire target study area, dividing it into 40-50 single sand body-level sedimentary units in the vertical direction.

[0016] Preferably, in step two, the transverse overlapping of the distributary sand bodies is of three types: thick-thin distributary sand bodies, elevation-difference distributary sand bodies, and scale-difference distributary sand bodies.

[0017] Preferably, in step three, the method for identifying the boundary points of the single channel boundary is to identify them by pulling the sand body connection profile and seismic inversion profile well by well and row by row along the transverse sand body distribution direction.

[0018] Preferably, in step four, the combination of the single channel boundaries of the overlapping sand bodies is such that the sand body profiles within the same channel start or end simultaneously.

[0019] Preferably, in step four, the sand body connectivity type includes poor sand body connectivity and no sand body connectivity. Poor sand body connectivity means that the water drive effect is not obvious and the tracer cannot be detected.

[0020] Preferably, in step five, the process of establishing the net-to-gross ratio and permeability attribute model of the small layer specifically involves dividing multiple channel sedimentary facies into multiple channel sand bodies developed in the same layer, setting different channel facies codes according to the different periods of sand body deposition, and using single-phase channel sedimentary facies for preliminary modeling of constraint difference.

[0021] Preferably, in step six, channel edge attribute constraints are performed before the establishment of the multi-phase channel constraint attribute model. The method for constraining channel edge attributes is to set virtual well points at the channel edge using a computer, assign values ​​to the virtual well points according to the thickness and permeability of the channel sand body profile, and interpolate the actual well point constraints in the target study area using the virtual well point attributes.

[0022] Preferably, in step seven, the formula for calculating the grid conductivity of the corrected channel boundary is:

[0023]

[0024] or

[0025] In the formula, T xs The corrected mesh conductivity along the x-axis, 10 -3 μm 3 ;T ys The corrected mesh conductivity along the y-axis, 10 -3 μm 3 Δx is the change in distance along the x-axis, in meters; Δy is the change in distance along the y-axis, in meters; H s The corrected height of the two-stage river channel contact surface, in meters (m); k xs To correct the permeability of the contact surface in the x-direction of the river channel in the latter two periods, 10 -3 μm.

[0026] (III) Beneficial Effects

[0027] The present invention provides a multi-stage channel contact relationship simulation method based on low-curvature distributary channel sedimentation. Based on well-seismic combined with fine geological data, it re-understands and describes multi-stage channel boundaries. Through single sand body boundary constraint attribute modeling and multi-stage channel boundary grid conductivity simulation, a geological modeling and numerical simulation method based on multi-stage channel contact relationships is formed. This method further improves the accuracy of history fitting and residual oil description in low-permeability reservoirs. It can not only accurately characterize residual oil in different parts of a single sand body, but also effectively guide the targeted and precise tapping of residual oil potential. Attached Figure Description

[0028] Figure 1 This is a flowchart illustrating a multi-stage channel contact relationship simulation method based on low-swerve distributary channel deposition, as described in an embodiment of the present invention.

[0029] Figure 2 A standard diagram for establishing single-well facies patterns in embodiments of the present invention;

[0030] Figure 3 This is the single river boundary well seismic identification mode in this embodiment of the invention;

[0031] Figure 4The above are well logging sedimentary facies maps in this embodiment of the invention, wherein a is the well logging sedimentary facies map of layer FIII2, b is the well-connected profile, c is the seismic inversion overlay profile, and d is the well-seismic combined sedimentary facies map of layer FIII2.

[0032] Figure 5 This is a diagram showing the result of identifying the boundary of a single river channel in an embodiment of the present invention.

[0033] Figure 6 This is a diagram showing the correspondence between connectivity and water drive status in an embodiment of the present invention;

[0034] Figure 7 This is a connectivity change identification diagram in an embodiment of the present invention, wherein a is a well logging sedimentary facies zone diagram of layer F162, b is a well-seismic combined sedimentary facies zone diagram of layer F162, and c is a tracer monitoring schematic diagram.

[0035] Figure 8 For identifying non-connected sand bodies in this embodiment of the invention, a is a well logging sedimentary facies map of layer FIII2, b is a well-seismic combined sedimentary facies map of layer FIII2, and c is a diagram showing the effect of measures before and after the treatment of wells Chao 63-89.

[0036] Figure 9 This is a diagram showing the assignment of channel facies codes in the sedimentary facies plane in an embodiment of the present invention.

[0037] Figure 10 This is a schematic diagram of multiple river channels in an embodiment of the present invention;

[0038] Figure 11 The diagram shows the variation patterns of physical properties and thickness in an embodiment of the present invention, where a represents the variation pattern of river channel permeability over multiple periods, and b represents the variation pattern of river channel thickness over multiple periods.

[0039] Figure 12 This is a distribution diagram of permeability and net-to-gross ratio before and after attribute constraint at the riverbank of FⅡ12 layer in an embodiment of the present invention. In the diagram, a is the permeability before attribute constraint, b is the permeability after attribute constraint, c is the net-to-gross ratio before attribute constraint, and d is the net-to-gross ratio after attribute constraint.

[0040] Figure 13 The diagram shows the changes in water cut curves before and after modifying the channel conductivity in the Chao 77-77 embodiment of the present invention. In the diagram, a is the sedimentary facies zone diagram of layer FIII2, b is the remaining oil saturation diagram of layer FIII2, c is the water cut fitting curve in the Chao 74-84, (I) is the initial simulation result, and (II) is the result after modifying the channel conductivity in the Chao 77-77 embodiment.

[0041] Figure 14 This is an oil saturation field diagram of layer FⅡ12 in an embodiment of the present invention, where a represents the area without considering river contact relationship, and b represents the area considering river contact relationship;

[0042] Figure 15This is a historical fitting curve of liquid production, water content, and cumulative oil production from Chao 5 to Chao 5 North in an embodiment of the present invention, where a is the liquid production, b is the comprehensive water content, and c is the cumulative oil production. Detailed Implementation

[0043] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] Figure 1 This is a flowchart illustrating a multi-stage channel contact relationship simulation method based on low-swerve distributary channel deposition, as described in an embodiment of the present invention. Figure 1 As shown, this invention provides a multi-stage channel contact relationship simulation method based on low-straightness distributary channel deposition, specifically including:

[0045] Step 1: Determine the target study area, divide the target study area into multiple single sand body-level sedimentary units, and establish single-well logging facies models based on the closed core wells in each single sand body-level sedimentary unit;

[0046] Step 2: Establish a seismic forward model based on the various types of transverse overlapping of distributary channel sand bodies, and in conjunction with the single-well logging facies model, obtain the well-seismic identification modes corresponding to each type of transverse overlapping of distributary channel sand bodies;

[0047] Step 3: Based on the acquired multiple well seismic identification patterns, identify the boundaries of individual river channels well by well and row by row within the target study area, and obtain the boundary points of each individual river channel boundary.

[0048] Step 4: Based on the identified multiple boundary points, combine them into a single channel boundary of overlapping sand bodies, and determine the sand body connectivity of the single channel boundary of overlapping sand bodies;

[0049] Step 5: Based on the single channel boundary identification results, combined with well point data and seismic data of each single sand body-level sedimentary unit, establish a small-layer net-to-gross ratio and permeability attribute model using the single-stage channel facies constraint difference method;

[0050] Step 6: Obtain multi-phase channel facies maps within the target study area, determine channel boundaries based on these maps, and establish multi-phase channel constraint attribute models in conjunction with the net-to-gross ratio and permeability attribute models of the sublayer.

[0051] Step 7: Correct the grid conductivity of the river boundary based on the multi-phase river constraint attribute model, establish a multi-phase river contact relationship simulation model, and characterize the type and location of remaining oil in the target study area through the calculation results of the simulation model.

[0052] In this simulation method, in step one, the method for dividing single sand body-level sedimentary units is based on the standard top and bottom layers and multi-stage flood surface reference layers in the target study area. First, the skeleton profile is closed and compared, and then the stratigraphic comparison is performed in the entire target study area, and 40-50 single sand body-level sedimentary units are divided vertically.

[0053] In practical applications, in step two, there are three types of transverse overlapping of distributary channel sand bodies: thick-thin-thin distributary channel sand bodies, elevation-difference distributary channel sand bodies, and scale-difference distributary channel sand bodies.

[0054] In this simulation method, in step three, the boundary point of a single channel boundary is identified by pulling the sand body connection profile and seismic inversion profile well by well and row by row along the transverse sand body distribution direction.

[0055] In practical applications, in step four, the combination of single channel boundaries of overlapping sand bodies is such that the sand body profiles within the same channel start or end simultaneously. The sand body connectivity types include poor sand body connectivity and no sand body connectivity. Poor sand body connectivity means that the water drive effect is not obvious and the tracer cannot be detected.

[0056] In this simulation method, in step five, the process of establishing the net-to-gross ratio and permeability attribute model of the small layer is specifically as follows: based on the division of multiple channel sedimentary facies, multiple channel sand bodies developed in the same layer are assigned different channel facies codes according to the different periods of sand body deposition, and a preliminary modeling of constraint difference is performed using a single-period channel sedimentary facies.

[0057] In practical applications, in step six, before establishing the multi-stage channel constraint attribute model, channel edge attribute constraints are performed. The method for constraining channel edge attributes is to set virtual well points at the channel edge using a computer, assign values ​​to the virtual well points according to the thickness and permeability of the channel sand body profile, and interpolate the constraints of the actual well points in the target study area using the virtual well point attributes.

[0058] In this simulation method, in step seven, the formula for calculating the grid conductivity of the corrected channel boundary is:

[0059]

[0060] or

[0061] In the formula, T xs The corrected mesh conductivity along the x-axis, 10 -3 μm 3 ;T ys The corrected mesh conductivity along the y-axis, 10 -3 μm 3Δx is the change in distance along the x-axis, in meters; Δy is the change in distance along the y-axis, in meters. The corrected height of the two-stage river channel contact surface, in meters (m). To correct the permeability of the contact surface in the x-direction of the river channel in the latter two periods, 10 -3 μm.

[0062] This invention provides a multi-stage channel contact relationship simulation method based on low-torsional distributary channel deposition. It comprehensively considers methods for quantitative characterizing remaining oil, including channel contact relationships, reservoir description, and reservoir numerical simulation. Through simulation of the time-varying effects of natural fractures, the accuracy of single-well water cut fitting is significantly improved. Furthermore, the description of planar interference-type remaining oil caused by multi-stage channel shading is more accurate, better guiding targeted and precise tapping of remaining oil potential. The working principle of this multi-stage channel contact relationship simulation method based on low-torsional distributary channel deposition is described in detail below:

[0063] In this embodiment, the target study area is determined and divided into multiple single-sandbody-level sedimentary units. Based on the closed core wells within each single-sandbody-level sedimentary unit, a single-well logging facies model is established. A seismic forward model is established based on various types of lateral overlap of distributary channel sand bodies. Combined with the single-well logging facies model, well-seismic identification patterns corresponding to each type of lateral overlap of distributary channel sand bodies are obtained. Based on the obtained well-seismic identification patterns, single-channel boundaries are identified well-by-well and row-by-row within the target study area, and the boundary points of each single-channel boundary are obtained. Based on the identified boundary points, a single-channel boundary of the overlapped sand bodies is formed, and the overlap is determined. The sand body connectivity of a single channel boundary in a sand body is investigated. Based on the single channel boundary identification results, combined with well point data and seismic data of each single sand body-level sedimentary unit, a sublayer net-to-gross ratio and permeability attribute model is established using the single-phase channel facies constraint difference method. Multi-phase channel facies maps are obtained within the target study area, and channel boundaries are determined based on these maps. In conjunction with the sublayer net-to-gross ratio and permeability attribute model, a multi-phase channel constraint attribute model is established. The grid conductivity of the channel boundary is corrected based on the multi-phase channel constraint attribute model, and a multi-phase channel contact relationship simulation model is established. The calculation results of the simulation model are used to characterize the remaining oil type and location within the target study area.

[0064] In practical applications, for the development of narrow strip and discontinuous strip channel sand bodies in low-permeability reservoirs around DQ, single sand body geological modeling technology is used to improve the accuracy of oil and gas history fitting and residual oil identification. For the originally large-area connected distributary channel sand bodies, during water injection development, the dynamic display shows that they are not connected or have poor connectivity, resulting in multi-segment and patchy water flooding of these reservoirs, with a large amount of residual oil in water drive. Due to the severe horizontal and vertical overlap of the actual distributary channel sand bodies, it is difficult to distinguish them vertically and horizontally.

[0065] In this embodiment, the target study area was selected as the Chaoyanggou Oilfield. The Fuyang oil layer in the Chaoyanggou Oilfield has three sedimentary facies: fluvial, deltaic lacustrine, and lacustrine (marsh) facies. Among them, fluvial sediments are the main type, consisting primarily of narrow-banded and discontinuous-banded channel sand bodies. Therefore, a multi-phase channel sedimentary facies classification study was conducted for the target study area. The characteristics of sand body thickness and permeability variation in a single channel profile and the contact relationships of channel sand bodies in multiple phases were statistically analyzed, providing a basis for attribute modeling and numerical simulation.

[0066] In practical applications, following the principle of phase-controlled cyclic isochronous correlation, and under the control of standard top and bottom layers and multi-stage floodplain reference layers, first, a framework profile closure correlation is performed, followed by a comprehensive stratigraphic correlation of the entire area, vertically dividing the area into 47 single-sandbody-level sedimentary units. It is important to note that, except for deep-cut sandstone bodies that can be equivalent to the same single sandbody in terms of development, vertical subdivision to single-sandbody-level sedimentary units is achieved, realizing vertical phasing of single sandbody units. Furthermore, as... Figure 2 As shown, based on the closed core wells within each single sand body-level sedimentary unit, well logging facies models are established through rock-electrical correspondence. According to the facies models, single-well sedimentary microfacies are identified on the plane, realizing single-well model facies determination.

[0067] In this embodiment, as Figure 3 As shown, the lateral overlap of distributary channel sand bodies can be divided into thick-thin distributary channel sand bodies, elevation-difference distributary channel sand bodies, and scale-difference distributary channel sand bodies. By establishing a seismic forward model, the well-seismic identification mode of the contact relationship among these three types of sand bodies is determined, and single channel boundaries are identified well-by-well and row-by-row. Figure 4 a to Figure 4 As shown in d, guided by three types of single-channel boundary well-seismic identification models, the sand body connectivity profiles and seismic inversion profiles are extracted well by well and row by row along the transverse sand body distribution direction for identification, as shown in d. Figure 5 As shown, following the principles of sedimentary model guidance and sand body orientation control, and adhering to the characteristic that sand body profiles within the same channel start or end simultaneously, they are combined to form a single channel boundary.

[0068] In practical applications, such as Figure 6 As shown, based on whether oil and water wells are located in the main river channel sand or non-main river channel sand, and whether they are located in the same river channel or different river channels, the connectivity is subdivided into three categories and eight subcategories to determine the strong and weak directions of water drive and guide the adjustment of water injection policies.

[0069] In this embodiment, after the identification of a single channel boundary, the changes in connectivity manifest in two types: deterioration of sand body connectivity and disconnection of sand bodies. First, in the case of poor sand body connectivity, before the identification of the single channel boundary, some Ia-connected oil wells within the same channel showed no effect from water injection adjustments. After identification, these wells and water wells no longer belong to the same channel and are classified as IIb-connected, resulting in poor water drive performance. Simultaneously, tracer monitoring shows no tracer activity, proving that the single channel identification is relatively accurate. For example, Figure 7a to Figure 7 As shown in c, 295 instances of connectivity deterioration were identified across the three blocks, guiding adjustments to the water injection structure in 187 wells, resulting in optimized production structure. Secondly, regarding sand body disconnectivity, before the identification of single channel boundaries, oil and water wells were connected but water injection adjustments were ineffective. After identification, pinch-out zones were delineated, and the oil and water wells became disconnected, consistent with the ineffective dynamic water injection situation. For example, Figure 8 a to Figure 8 As shown in c, 76 disconnected wells were identified in the three blocks, guiding CO2 injection and fracturing measures in 101 wells. For example, in the Chao 62-88 well group: after well-seismic integration, the Chao 63-89 well and the Chao 62-88 well changed from being connected to being disconnected, forming an isolated well point. In March 2022, CO2 injection was implemented, initially increasing the daily oil production of a single well by 0.8t, with a cumulative increase of 99t.

[0070] In practical applications, for multi-stage channels, the sedimentary environment and physical properties of single-stage channel sand bodies are similar, while the sedimentary environment and physical properties of channels in different stages are different. Therefore, the attribute modeling process splits the channel facies and constrains it according to the single-stage channel facies.

[0071] In this embodiment, to reflect the differences between different channel sand bodies, based on the results of multi-stage channel sedimentary facies classification, multiple channel sand bodies developed in the same layer are assigned different channel facies codes according to the different depositional periods of the sand bodies. During attribute modeling, single-stage channel sedimentary facies is used to constrain the difference. For example... Figure 9 As shown, the Chao 5 North FⅡ12 and FⅠ22 oil layers are divided into 6 and 7 channel phases in plan view, which are named hd1, hd2, hd3, hd4, hd5, hd6, and hd7, respectively. It is important to note that, based on well point data and seismic data of each individual sandbody-level sedimentary unit, a single-phase channel facies-constrained difference method is used to establish the net-to-gross ratio and permeability attribute model for each layer.

[0072] In practical applications, due to the small scale and narrowness of the single-stage channel development in the Chaoyangou oilfield, and the limited number of well points encountered at the channel edges, the problem of abrupt changes in sand body thickness and permeability at the channel edges cannot be solved even with the adoption of single-stage channel facies constraints.

[0073] In this embodiment, the riverbank attribute constraint method is used to constrain the interpolation. Since the riverbank attribute constraint method requires difference calculation, which is labor-intensive, a data processing program is developed to automatically process the data into the data received by the PETREL software in order to solve the problem.

[0074] The specific approach involves using a computer program to automatically locate river boundaries based on a digitized multi-phase river facies map. Virtual well coordinates are then established at the riverbanks. The program automatically searches for actual well points around the virtual wells, combining the variation patterns of sand body thickness and permeability with the well point differences to provide the top depth, thickness, and permeability attributes of the virtual wells. This constrains and controls attribute interpolation, enabling the accurate description of attribute differences across multiple river phases.

[0075] In practical applications, such as Figure 10 As shown, based on multi-stage channel sedimentary facies maps, the relationship between permeability and distance to the channel center at different locations of a single channel sand body was studied. To obtain regular data, permeability and distance were first subjected to dimensionless processing.

[0076]

[0077] It is important to note that k 中 Permeability of the central part of the river channel, 10 -3 μm 2 ;k r The permeability at a distance r from the center of the river channel, 10 -3 μm 2 ; r is the distance to the center of the river channel, in meters; R is the distance from the edge to the center of the river channel, in meters.

[0078] It should be noted that the permeability in the center of the river channel is obtained by averaging the permeability of wells located in the center of the river channel.

[0079] In this embodiment, as Figure 11 a and Figure 11 As shown in b, the permeability distribution of 285 wells along the river channel profile was statistically analyzed. Within 4 / 5 of the distance from the center of the river channel, the reservoir permeability did not change much. However, when the distance from the center of the river channel exceeded 4 / 5, the reservoir permeability dropped sharply, and the permeability at the edge of the river channel was only about 0.46 times that of the middle section.

[0080] In practical applications, curve fitting of the permeability distribution data of river sand bodies revealed a logarithmic law, i.e.

[0081]

[0082] First, the dimensionless permeability of the virtual well is calculated using formula (3). Then determine the permeability k at the middle position of the river channel corresponding to the virtual well. 中 Finally, substituting into formula (1), we obtain the permeability k of the virtual well at the riverbank. r The virtual well sandstone top depth is obtained based on the difference between the actual well point data and the data. The method for processing the virtual well sandstone thickness is similar to that for permeability.

[0083] In this embodiment, through program processing, a total of 650 virtual wells are set at the edges of the multi-stage river channels in the main layers FⅡ11 and FⅡ12. The permeability is assigned according to the interpolated top and bottom depths. Then, interpolation modeling is performed under the single-stage river channel facies constraint conditions to create the attribute model.

[0084] In practical applications, based on a three-dimensional structural model, a combination of digital and modeling software is used to complete the sedimentary facies model. The sedimentary facies zone map from detailed geological studies is used as a constraint condition, and the facies model is established using an assignment simulation method. In this embodiment, the sedimentary facies of Chao 5 North mainly include mudstone, channel sand, abandoned channel sand, interfluvial sand, and surface sand. The established sedimentary facies model, such as... Figure 12 a to Figure 12 As shown in d, neither the net-to-gross ratio nor the permeability attribute exhibits the characteristic of being high in the middle and low at the edges of the channel sand body. This is inconsistent with the thickness and permeability variation characteristics of the channel sand body profile mentioned earlier. Typically, channel contact relationships are not considered during the simulation process, and the attributes at the junctions between oil and water wells and between multiple channel phases are obtained by interpolation from well point data. If the net-to-gross ratio and permeability attribute values ​​of the well points on both sides of the junction of multiple channel phases are large, the interpolated attributes at the channel boundary are higher than the actual values. After considering the channel contact relationship and constraining the attributes at the channel edges, the attribute characteristics of the single-phase channel sand body are obvious, that is, the net-to-gross ratio and permeability are high in the middle and low at the edges. There are also significant differences in the sand body attributes between multiple channel phases, which improves the simulation accuracy and provides a more realistic geological model for subsequent numerical simulation studies of the distribution of remaining oil.

[0085] In this embodiment, in previous numerical simulations, the influence of multi-stage channel contact relationships on sand body connectivity was generally not considered. The connectivity between individual sand bodies, i.e., conductivity, was calculated only based on grid permeability. The influence of contact area and contact surface permeability was ignored, resulting in conductivity that was significantly higher than the actual value and the distribution of residual oil at the riverbank was not obvious.

[0086] In practical applications, conventional numerical simulation methods do not consider the influence of multi-stage river contact boundaries on grid conductivity. The water cut of single wells on both sides of the river rises rapidly, making it difficult to fit the water cut of a single well. By correcting the grid conductivity at the river boundary, the simulation of multi-stage river contact relationships can be achieved, which can significantly improve the water cut of oil wells at the river boundary.

[0087] In this embodiment, the influence of multi-stage river contact relationships is not considered, and the grid conduction rate at the river boundary is...

[0088]

[0089] or

[0090] Considering the influence of multi-stage river contact relationships, the transmission rate of the grid where the river boundary is located is...

[0091]

[0092] or

[0093] In the formula, The average thickness of the channel sand body in the two phases, in meters; The average permeability along the river channel for the two periods, 10 -3 μm 2 ;T x The grid conductivity is 10 along the x-axis. -3 μm 3 ;T y The grid conductivity in the y-axis direction is 10. -3 μm 3 ;T xs The corrected mesh conductivity along the x-axis, 10 -3 μm 3 ;T ys The corrected mesh conductivity along the y-axis, 10 -3 μm 3 Δx is the change in distance along the x-axis, in meters; Δy is the change in distance along the y-axis, in meters; H s The corrected height of the two-stage river channel contact surface, in meters (m). To correct the permeability of the contact surface in the x-direction of the river channel in the latter two periods, 10 -3 μm.

[0094] Therefore, the conductivity multiplier in the x or y direction of the boundary mesh

[0095] or

[0096] Table 1 shows the reference range of conductivity multiplier for different contact relationships in multiple river phases. As shown in Table 1, based on the research results of contact relationships in multiple river phases, the reference range of conductivity multiplier for the grid where the contact boundary of multiple river phases is located is calculated using the formula.

[0097] Table 1. Reference range of conductance multiplier for different contact relationships in multi-period river channels.

[0098]

[0099] In practical applications, such as Figure 13 a, Figure 13 b、 Figure 13 c(I) and Figure 13As shown in c(II), taking Chao 77-77 well as an example, Chao 77-77 well is located on the left side of the northern boundary of the river channel, and the water injection well Chao 78-78 on the right side of the river channel boundary is connected to it. Without considering the influence of the contact relationship between the river channel sand bodies, the connectivity between the sand bodies is good, and the water well has a great influence on the oil well Chao 77-77 well. The calculated water cut rises quickly, and the water cut fitting error is large. After reducing the conductivity at the river channel boundary, the water cut fitting error is significantly reduced, and the fitting effect is good.

[0100] In this embodiment, after simulating the contact relationship of multiple river channels, the calculation process demonstrated the shielding effect of the multiple river channel boundaries on oil-water flow, thus improving the accuracy of residual oil characterization at the river channel boundaries. For example... Figure 14 a and Figure 14 As shown in b, comparing the changes in the simulated oil saturation field with and without considering boundary grid conductivity correction, the numerical simulation does not consider the influence of channel contact relationship on water drive development, and the calculated oil saturation at the channel contact boundary is low, about 45.87%; after considering the channel contact relationship, the remaining oil is enriched at the channel edge, and the accuracy of the calculated oil saturation is improved by 4.61 percentage points.

[0101] In practical applications, such as Figure 15 a to Figure 15 As shown in Figure c, the fitting curves for liquid production, water cut, and cumulative oil production in the Chao 5 North Block show that the fitting accuracy for liquid production up to December 2022 is relatively high. The actual comprehensive water cut is 66.72%, and the actual cumulative oil production is 4.003 million tons. Using the simulation technology mentioned above, the calculated comprehensive water cut is 66.85%, and the absolute error of the water cut has decreased from 0.95% to 0.13%, improving the calculation accuracy by 0.82 percentage points. The calculated cumulative oil production is 3.9903 million tons, and the relative error of the cumulative oil production has decreased from 1.29% to 0.32%, improving the calculation accuracy by 0.97 percentage points. All of the above indicators meet the accuracy requirements.

[0102] The present invention provides a multi-stage channel contact relationship simulation method based on low-curvature distributary channel sedimentation. Based on well-seismic combined with fine geological data, it re-understands and describes multi-stage channel boundaries. Through single sand body boundary constraint attribute modeling and multi-stage channel boundary grid conductivity simulation, a geological modeling and numerical simulation method based on multi-stage channel contact relationships is formed. This method further improves the accuracy of history fitting and residual oil description in low-permeability reservoirs. It can not only accurately characterize residual oil in different parts of a single sand body, but also effectively guide the targeted and precise tapping of residual oil potential.

[0103] The above embodiments are only used to illustrate the present invention and are not intended to limit the present invention. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, all equivalent technical solutions also fall within the scope of the present invention, and the patent protection scope of the present invention should be defined by the claims.

Claims

1. A multi-stage channel contact relationship simulation method based on low-straightness distributary channel deposition, characterized in that, include: Step 1: Determine the target study area, divide the target study area into multiple single sand body-level sedimentary units, and establish single-well logging facies models based on the closed core wells in each single sand body-level sedimentary unit; Step 2: Establish a seismic forward model based on the various types of transverse overlapping of distributary channel sand bodies, and in conjunction with the single-well logging facies model, obtain the well-seismic identification modes corresponding to each type of transverse overlapping of distributary channel sand bodies; Step 3: Based on the acquired multiple well seismic identification patterns, identify the boundaries of individual river channels well by well and row by row within the target study area, and obtain the boundary points of each individual river channel boundary. Step 4: Based on the identified multiple boundary points, combine them into a single channel boundary of overlapping sand bodies, and determine the sand body connectivity of the single channel boundary of overlapping sand bodies; Step 5: Based on the single channel boundary identification results, combined with well point data and seismic data of each single sand body-level sedimentary unit, establish a small-layer net-to-gross ratio and permeability attribute model using the single-stage channel facies constraint difference method; Step 6: Obtain multi-phase channel facies maps within the target study area, determine channel boundaries based on these maps, and establish multi-phase channel constraint attribute models in conjunction with the net-to-gross ratio and permeability attribute models of the sublayer. Step 7: Correct the grid conductivity of the river boundary based on the multi-phase river constraint attribute model, establish a multi-phase river contact relationship simulation model, and characterize the type and location of remaining oil in the target study area through the calculation results of the simulation model.

2. The method for simulating multi-stage channel contact relationships based on low-straightness distributary channel deposition according to claim 1, characterized in that, In step one, the method for dividing the single sand body-level sedimentary units is based on the standard top and bottom layers and multi-stage floodplain reference layers in the target study area. First, the skeleton profile is closed and compared, and then the overall stratigraphic comparison is performed in the entire target study area, dividing it into 40-50 single sand body-level sedimentary units in the vertical direction.

3. The method for simulating multi-stage channel contact relationships based on low-straightness distributary channel deposition according to claim 1, characterized in that, In step two, there are three types of transverse overlapping of the distributary sand bodies: thick-thin distributary sand bodies, elevation-difference distributary sand bodies, and scale-difference distributary sand bodies.

4. The method for simulating multi-stage channel contact relationships based on low-straightness distributary channel deposition according to claim 1, characterized in that, In step three, the method for identifying the boundary points of the single channel boundary is to identify them by pulling the sand body connection profile and seismic inversion profile well by well and row by row along the transverse sand body distribution direction.

5. The method for simulating multi-stage channel contact relationships based on low-straightness distributary channel deposition according to claim 1, characterized in that, In step four, the combination of the single channel boundary of the overlapping sand bodies is such that the sand body profiles within the same channel start or end simultaneously.

6. The method for simulating multi-stage channel contact relationships based on low-straightness distributary channel deposition according to claim 1, characterized in that, In step four, the sand body connectivity type includes poor sand body connectivity and no sand body connectivity. Poor sand body connectivity means that the water drive effect is not obvious and the tracer cannot be detected.

7. The method for simulating multi-stage channel contact relationships based on low-straightness distributary channel deposition according to claim 1, characterized in that, In step five, the process of establishing the net-to-gross ratio and permeability attribute model of the small layer is specifically as follows: based on the division of multiple channel sedimentary facies, multiple channel sand bodies developed in the same layer are assigned different channel facies codes according to the different periods of sand body deposition, and preliminary modeling of constraint difference is performed using single-phase channel sedimentary facies.

8. The method for simulating multi-stage channel contact relationships based on low-straightness distributary channel deposition according to claim 1, characterized in that, In step six, before establishing the multi-phase channel constraint attribute model, channel edge attribute constraints are performed. The method for constraining channel edge attributes is to set virtual well points at the channel edge using a computer, assign values ​​to the virtual well points according to the thickness and permeability of the channel sand body profile, and interpolate the actual well point constraints in the target study area using the virtual well point attributes.

9. The method for simulating multi-stage channel contact relationships based on low-straightness distributary channel deposition according to claim 1, characterized in that, In step seven, the formula for calculating the grid conductivity of the corrected channel boundary is: or In the formula, T xs The corrected mesh conductivity along the x-axis, 10 -3 μm 3 ; T ys The corrected mesh conductivity along the y-axis, 10 -3 μm 3 Δx is the change in distance along the x-axis, in meters; Δy is the change in distance along the y-axis, in meters. The corrected height of the two-stage river channel contact surface, in meters (m). To correct the permeability of the contact surface in the x-direction of the river channel in the latter two periods, 10 -3 μm.

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