Three-dimensional geological model quality control method and device

Abstract

The invention discloses a three-dimensional geologic model quality control method and device, and the method comprises the steps: carrying out the quality control of a fault model in a structural framework model; performing quality control on a layer model in the construction framework model; performing quality control on a grid model in the constructed framework model; performing quality control on the phase model; performing quality control on the reservoir parameter model; performing comprehensive quality control on the facies model and the reservoir parameter model; performing quality control on the new saturation model; and performing quality control on a reserve calculation result obtained based on the three-dimensional geologic model. According to the method, systematic and perfect quality control is carried out on the three-dimensional geologic model, problems existing in the modeling process can be explored, the part, which does not meet the quality standard, of the three-dimensional geologic model is further analyzed and then improved, the quality of the three-dimensional geologic model can be improved, and geological knowledge can be even updated under some conditions; and the understanding of the oil reservoir is further deepened.

Description

Technical Field

[0001] The present invention belongs to the technical field of oil and gas development, and in particular relates to a method and device for quality control of a three-dimensional geological model. Background Art

[0002] 3D geological models are a key component of reservoir characterization. They integrate various reservoir research studies and fully reflect the state of reservoir understanding. These models include a structural framework model, a facies model, and a reservoir parameter model. Using these models, combined with historical matching, they enable production forecasting and development plan optimization, making them a crucial tool for reservoir management. Currently, 3D geological modeling is widely used in reservoir development, especially in major domestic oil and gas fields such as the Changqing and Tarim oilfields.

[0003] Quality control of 3D geological models determines model quality and the foundation for subsequent reservoir engineering research, making it a crucial step in modeling. However, limited research is currently underway in this area, both domestically and internationally. Current methods are limited to input data quality control, grid morphology control for different model angles, well sampling verification, and rapid history matching. However, the lack of a systematic and comprehensive quality control process often makes it difficult to ensure model quality. A systematic 3D geological model quality control approach will raise the bar for model quality control, further improving model quality and providing a solid foundation for oil and gas field exploration and development. Summary of the Invention

[0004] In response to the above problems, the present invention discloses a method for quality control of a three-dimensional geological model, comprising:

[0005] Conduct quality control on the fault model in the structural framework model;

[0006] Conduct quality control on the level models in the construction framework model;

[0007] Conduct quality control on the mesh model in the construction framework model;

[0008] Perform quality control on the phase model;

[0009] Perform quality control on reservoir parameter models;

[0010] Comprehensive quality control of facies models and reservoir parameter models;

[0011] Perform quality control on the new saturation model;

[0012] Perform quality control on reserve calculation results based on 3D geological models.

[0013] Furthermore, the specific steps of performing quality control on the fault model in the structural framework model are as follows:

[0014] Analyze fault attributes;

[0015] Draw the fault throw distribution map of each fault, and determine whether the fault throw at the fault edge of each fault is less than or equal to the fault throw in the middle of the fault; judge whether the fault throw value in the fault model conforms to the fault throw distance of the seismic event or the fault throw value confirmed by well logging data; if both are yes, the quality of the fault model is good.

[0016] Furthermore, the specific steps for quality control of the horizon model in the structural framework model are as follows:

[0017] Judge whether there is a phenomenon of altitude change in the horizon model;

[0018] If so, determine the altitude change coefficient H of the horizon model;

[0019] When H < 5, the grid quality of the horizon model is good; when 5 < H < 10, the grid quality of the horizon model is average; when H > 10, the grid quality of the horizon model is poor;

[0020] The altitude change coefficient is determined by the following formula:

[0021]

[0022] where D i is the altitude of the i-th grid within the first threshold of the perimeter of the calculated grid; D a is the geometric mean of the altitudes of all grids within the first threshold of the perimeter of the calculated grid; n is the number of grids within the first threshold of the perimeter of the calculated grid; D c is the grid width.

[0023] Furthermore, the quality control of the horizon model in the structural framework model also includes the following steps:

[0024] Draw a histogram of the thickness of each sub-layer and analyze whether the thickness distribution conforms to geological understanding;

[0025] Draw the formation thickness map of each sub-layer, observe whether the formation thickness change conforms to the structural style and sedimentary environment, and judge whether there is a change within the set range of formation thickness;

[0026] If so, determine the reservoir thickness change coefficient M;

[0027] When M > 0.7, it is considered that the formation thickness changes rapidly;

[0028] The reservoir thickness change coefficient M is determined by the following formula:

[0029]

[0030] Among them, A i is the reservoir thickness value of the i-th grid within the first threshold distance around the calculated grid; A a is the geometric mean of the reservoir thickness values of all grids within the first threshold distance around the calculated grid; n is the number of grids within the first threshold distance around the calculated grid.

[0031] Furthermore, the specific steps for quality control of the grid model in the structural framework model are as follows:

[0032] Judge the quality of a single grid in the grid model;

[0033] When the thickness h of a single grid > 0.5m, the volume V > 0, and the angle 0° < C < 5°, the grid is considered to have good quality; or

[0034] When the volume V of a single grid > 0 and 0 < Q < 15, the grid is considered to have good quality;

[0035] Among them, the grid quality coefficient Q = C / h.

[0036] [[ID=​​​​​​​​​​​​​​​​​​​​​

[0043] Furthermore, the specific steps of performing comprehensive quality control on the facies model and the reservoir parameter model are as follows:

[0044] Draw the porosity and permeability crossplots of different sedimentary facies. The porosity and permeability crossplots of different sedimentary facies in the porosity model and permeability model should match the porosity and permeability crossplot characteristics of different sedimentary facies in the logging curve.

[0045] Furthermore, the specific steps of performing quality control on the new saturation model are as follows:

[0046] For individual well locations before production or injection begins in the reservoir, the saturation values ​​in the new saturation model should match the saturation values ​​interpreted from the well logs.

[0047] Furthermore, the specific steps of performing quality control on the reserve calculation results obtained based on the three-dimensional geological model are as follows:

[0048] Analyze whether there are any differences between the reserve calculation results and the original reserve calculation results. If there are any differences, analyze the differences between the new and old structural maps, the differences in free water interfaces, and the differences in oil-bearing areas;

[0049] Draw the porosity distribution histogram of the new porosity model and the old porosity model, and analyze the distribution difference between the new porosity model and the old porosity model;

[0050] Draw the water saturation distribution histogram of the new saturation model and the old saturation model, and analyze the distribution difference between the new saturation model and the old saturation model.

[0051] The present invention also discloses a device for controlling the quality of a three-dimensional geological model, comprising:

[0052] Fault model unit, used to perform quality control on the fault model in the tectonic framework model;

[0053] Level model unit, used to perform quality control on level models in the construction framework model;

[0054] Grid model unit, used to perform quality control on the grid model in the construction framework model;

[0055] Phase model unit, used for quality control of phase models;

[0056] Reservoir parameter model unit, used for quality control of reservoir parameter model;

[0057] Comprehensive unit for comprehensive quality control of facies model and reservoir parameter model;

[0058] A new saturation model unit, used for quality control of the new saturation model;

[0059] The reserve calculation unit is used to perform quality control on the reserve calculation results obtained based on the three-dimensional geological model.

[0060] Compared with the prior art, the embodiments of the present invention have at least the following advantages:

[0061] 1. Carrying out a more systematic and comprehensive quality control of the 3D geological model can identify problems in the modeling process and further analyze and improve the parts of the 3D geological model that do not meet the quality standards. This can improve the quality of the 3D geological model and in some cases even update geological understanding and further deepen the understanding of the reservoir.

[0062] 2. Complete quality control can effectively guarantee the quality of the 3D geological model, providing a solid foundation for the next step of reservoir numerical simulation, development plan preparation, and reservoir management.

[0063] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures pointed out in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0065] Figure 1 A flow chart showing a method for quality control of a three-dimensional geological model according to an embodiment of the present invention is shown;

[0066] Figure 2 shows a three-dimensional distribution diagram of a fault plane according to an embodiment of the present invention;

[0067] Figure 3 shows a three-dimensional distribution diagram of fault combinations according to an embodiment of the present invention;

[0068] Figure 4 shows a fault throw distribution diagram according to an embodiment of the present invention;

[0069] Figure 5 shows a cross-sectional view of a structure according to an embodiment of the present invention;

[0070] Figure 6 shows a plane distribution diagram of the altitude variation coefficient H of the oil reservoir B layer according to an embodiment of the present invention;

[0071] Figure 7 shows a distribution histogram of the altitude variation coefficient H of the oil reservoir B layer according to an embodiment of the present invention;

[0072] Figure 8 shows a histogram of the thickness of the small layer B in the reservoir according to an embodiment of the present invention;

[0073] Figure 9 The distribution of the grid quality coefficient Q of the oil reservoir B layer according to an embodiment of the present invention is shown;

[0074] Figure 10 shows a trend diagram used in modeling different position phase models and sedimentary phases according to an embodiment of the present invention;

[0075] Figure 11 The diagram shows the well logging data of the reservoir B layer, the model coarsening data and the data distribution diagram in the model according to an embodiment of the present invention;

[0076] Figure 12 shows the average porosity and average permeability distribution diagram of sedimentary phase I of layer B of the reservoir according to an embodiment of the present invention;

[0077] Figure 13 A comparison diagram of the porosity and permeability model data, model coarsening data, and well logging data distribution of the sedimentary phase I of the oil reservoir B layer according to an embodiment of the present invention is shown;

[0078] Figure 14 shows a cross-plot of porosity and permeability of different sedimentary phases of layer B of an oil reservoir according to an embodiment of the present invention;

[0079] Figure 15 A comparison diagram of the water saturation of N wells and the interpreted water saturation in the three-dimensional new saturation model according to an embodiment of the present invention is shown;

[0080] Figure 16 A top surface comparison diagram of the new and old structures of the B layer of the oil reservoir according to an embodiment of the present invention is shown;

[0081] Figure 17 A comparison diagram of porosity distribution between the new porosity model and the old model according to an embodiment of the present invention is shown;

[0082] Figure 18 A distribution comparison diagram of the new saturation model and the old saturation model according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0083] 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 in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0084] The existing 3D geological model quality control technology mainly includes three aspects: structural framework model, reservoir parameter model and reserve calculation.

[0085] For the quality control of the structural framework model, generally only the fault morphology and the orthogonality and distortion degree of the relevant grid are observed, while the parameters that really have a greater impact, such as the fault throw and the change of stratum thickness, are not considered.

[0086] For the quality control of reservoir parameter models, the current means are only to control the quality of reservoir parameter models based on geological knowledge. There are also methods to control the quality by comparing the distribution of input curve values ​​with the distribution of values ​​in the geological model, but the relationship between different parameters is not really considered.

[0087] The quality control of reserve calculation currently focuses on analyzing changes in oil-bearing area, effective thickness, etc., while changes in porosity, saturation, etc. are not fully considered.

[0088] At present, there is no effective method or technology for quality control of three-dimensional geological models, which is a key problem that needs to be solved urgently in oilfield exploration and development.

[0089] The 3D geological model includes a structural framework model, a facies model, and a reservoir parameter model. The structural framework model includes a fault model, a layer model, and a grid model. The 3D geological model is constructed during the initial exploration process using conventional techniques for the exploration area based on drilling data. This invention performs quality control on the constructed 3D geological model and, based on identified issues, provides recommendations or directions for improving the 3D geological model. The method for constructing the 3D geological model will not be detailed here; existing techniques can be used for its construction.

[0090] like Figure 1 As shown, the present invention proposes a method for quality control of a three-dimensional geological model, comprising the following steps:

[0091] Step S101: Based on the geological conditions of the study area, determine the structural style and sedimentary environment of the reservoir; general structural styles include monocline structure, anticline structure, nose structure, etc. Sedimentary environments include meandering river, delta front, intertidal zone, etc.

[0092] Step S102: Conduct quality control on the fault model in the structural framework model.

[0093] Observe the fault properties (normal fault / reverse fault / strike-slip fault), and judge whether they conform to geological understanding; whether there are deformities or mutations in the fault plane morphology; whether the combination relationship between faults conforms to geological understanding; then draw the throw distribution map of each fault, and observe whether the throw d distribution increases with the increase of the distance from the fault edge (that is, judge whether the throw at the fault edge of each fault is less than or equal to the throw in the middle of the fault); determine whether the throw d value in the fault model conforms to the throw value confirmed by the seismic event axis offset distance or well logging data; if all are yes, the fault model has good quality.

[0094] Step S103: Conduct quality control on the horizon model in the structural framework model;

[0095] Observe whether there is a sudden change in the altitude of the horizon model, and analyze the reason. If so, calculate the altitude change coefficient H; <0000​​​​​​​​​​​​​​​​​​​​​​​​​​​

[0103] When M > 0.7, it is considered that the formation thickness changes rapidly;

[0104] Define the reservoir thickness change coefficient M:

[0105]

[0106] In the formula, M is the reservoir thickness change coefficient, and A i is the reservoir thickness value of the i-th grid within the first threshold distance around the calculated grid; A a is the geometric mean of the reservoir thickness values of all grids within the first threshold distance around the calculated grid; n is the number of grids within the first threshold distance around the calculated grid.

[0107] When M > 0.7, it is considered that the formation thickness changes relatively fast and its rationality needs to be further verified. In the general layer model, the number of grids with relatively fast formation thickness changes should be less than 10% of the total number, but the upper limit value also needs to be determined through specific analysis according to the situation.

[0108] Step S104: Perform quality control on the grid model in the structural framework model;

[0109] The grid model includes the thickness h of the grid, the volume V of the grid, and the angle C of the grid.

[0110] Judge the quality of a single grid in the grid model;

[0111] When the thickness h of a single grid > 0.5 m, V > 0, and 0° < C < 5°, it is considered that the quality of this grid is good.

[0112] Define the quality coefficient Q of a single grid, Q = C / h, where the unit of C is ° and the unit of h is m. When V > 0 and 0 < Q < 15, it is considered that the grid quality is good. The proportion of grids with good quality in the entire grid model should be higher than 90%.

[0113] Step S105: Perform quality control on the facies model;

[0114] If the sedimentary facies trend is the same within a single layer, check whether the sedimentary facies trend map in the facies model is consistent with the trend used during sedimentary facies modeling; if it is consistent, the quality of the facies model is good; Figure 1 If different sedimentary trends appear within a single layer, check whether the facies models at different vertical positions are consistent with the trend maps used during sedimentary facies modeling respectively; if they are consistent, the quality of the facies model is good;

[0115] When different sedimentary trends appear within a single layer, check whether the facies models at different vertical positions are consistent with the trend maps used during sedimentary facies modeling respectively; if they are consistent, the quality of the facies model is good;

[0116] A sedimentary facies distribution histogram is plotted. When a trend-controlled facies model is not used, the facies model is considered of good quality if the well logging data, model coarsening data, and data from the facies model match. "Matched" means the absolute difference between any two of these three data sets is less than a second threshold. For example, the second threshold is 10%. It should be noted that the threshold is set based on the geological conditions of the study area and varies from one study area to another, so it can be adjusted based on the specific conditions of the study area.

[0117] Step S106: performing quality control on the reservoir parameter model;

[0118] Draw a planar distribution map of porosity and permeability for each layer and each sedimentary phase. The changes in porosity and permeability in the planar distribution map must be consistent with geological knowledge;

[0119] A distribution histogram of porosity and permeability is drawn for each interval and each sedimentary phase. When the well logging data, model coarsening data, and data in the reservoir parameter model match (wherein, matching means that the absolute value of the difference between any two of the above three data is less than the third threshold. Exemplarily, the third threshold is 10%); and the maximum, minimum, and average values ​​of the attributes (porosity and permeability) of each interval and each sedimentary phase match (that is, the absolute value of the difference between any two of the above three is less than the fourth threshold. Exemplarily, the fourth threshold is 10%), the reservoir parameter model is considered to be of good quality. The well logging data is the original data. First, the well logging curve is coarsened to obtain the model coarsening data, and then the coarsening curve is used for modeling to obtain the reservoir parameter model.

[0120] Step S107: performing comprehensive quality control on the facies model and the reservoir parameter model;

[0121] Plot the porosity and permeability crossplots of different sedimentary facies. The porosity and permeability crossplots of different sedimentary facies in the porosity and permeability models should match the porosity and permeability crossplots of different sedimentary facies in the well logs. This indicates that the facies model and reservoir parameter model are of good quality. "Match" means that the overlap between the two crossplots is greater than a fifth threshold. For example, the fifth threshold is 80%.

[0122] Step S108: performing quality control on the new saturation model;

[0123] For the location of a single well before production or injection begins in the reservoir, the saturation value in the new saturation model should match the saturation value interpreted from well logging, indicating that the new saturation model is of good quality. The saturation model is derived based on a structural framework model, a facies model, a saturation height function, and a reservoir parameter model. Matching means that the absolute difference between the two values ​​is less than a sixth threshold. Exemplarily, the sixth threshold is 15%.

[0124] Step S109: performing quality control on the reserve calculation results obtained based on the three-dimensional geological model.

[0125] Analyze whether there are any differences between the reserve calculation results and the original reserve calculation results. If there are any differences, analyze the differences between the new and old structural maps, the differences in free water interfaces, and the differences in oil-bearing areas;

[0126] The porosity distribution histograms of the new porosity model and the old porosity model are drawn to analyze the distribution differences between the new porosity model and the old porosity model. It should be noted that the new porosity model is improved and optimized based on the previous version of the old porosity model.

[0127] A water saturation distribution histogram was plotted for the new and old saturation models to analyze their differences. Reservoir reserves were calculated based on the structural framework model, facies model, and reservoir parameter model. The new saturation model was developed by improving and optimizing the previous version of the old saturation model.

[0128] After completing the above quality control and improving the corresponding content, the 3D geological model can be put into use.

[0129] The method for quality control of 3D geological models proposed in the present invention performs relatively systematic and comprehensive quality control on 3D geological models, can identify problems existing in the modeling process, further analyze and improve parts of the 3D geological model that do not meet quality standards, thereby improving the quality of the 3D geological model and, in some cases, even updating geological understanding and further deepening the understanding of oil reservoirs. Through complete quality control, the quality of the 3D geological model can be effectively guaranteed, providing a solid foundation for the next steps of numerical simulation of oil reservoirs, preparation of development plans, and oil reservoir management.

[0130] The method of the present invention is used to perform quality control on a three-dimensional geological model of a carbonate oil reservoir.

[0131] Step 1: Based on the geological conditions of the study area, determine the structural style and sedimentary environment of the reservoir.

[0132] This carbonate reservoir is a typical wide and gentle anticline structure, deposited in a confined environment of proximal carbonate sedimentation, subdivided into a gentle slope within the subtidal zone and a tidal flat within the intertidal zone. Faults in the reservoir are primarily strike-slip faults, trending nearly northwest-southeast, and are nearly vertical. Fault throws in the main reservoir area are relatively small, approximately 2 meters.

[0133] Step 2: Perform quality control on the fault model.

[0134] First, the fault model shows that the fault is a strike-slip fault, which is consistent with geological knowledge. Then the fault surface is observed and it is found that the fault surface is flat as a whole (such as Figure 2As shown, the fault combination conforms to the geological understanding (such as Figure 3 shown). Then, draw the fault throw distribution map, analyze each fault one by one, and find that the fault throw is smaller at the edge of the fault and larger in the middle of the fault, and the overall quality is good (such as Figure 4 shown). Measure the fault throw. For example, in the middle of the work area, seismic interpretation shows that the fault throw is about 2m. After verification, the fault throw at this position in the model is also about 2m, meeting the requirements (such as Figure 5 shown), so the quality of the fault model is good.

[0135] Step 3: Control the quality of the horizon model in the structural framework model.

[0136] Taking the B layer of this oil reservoir as an example, the research process is introduced below. First, observe the sudden change phenomenon of the elevation of the horizon model. By calculating the elevation change coefficient H (such as Figure 6 , Figure 7 shown), it is found that the number of grids with poor grid quality in the horizon model is less than 5% of the total number, meeting the quality control requirements.

[0137] Draw the formation thickness map and the formation thickness histogram of each sub-layer. Since this set of formations is carbonate platform deposition in a restricted environment and the overall terrain is relatively flat, the formation thickness change should be small. Calculate the reservoir thickness change coefficient M. When M>0.7, it is considered that the formation thickness changes rapidly and its rationality needs to be further verified. The result shows that the number of grids with rapid formation thickness change in the model is less than 10% of the total number, and the quality is considered good. At the same time, observe the formation thickness histogram of each sub-layer and find that the overall change of the layer thickness is small and the thickness is normally distributed, conforming to the existing geological understanding (such as Figure 8 shown).

[0138] Step 4: Control the quality of the grid model in the structural framework model.

[0139] Taking the B layer of this oil reservoir as an example, the research process is introduced below. Calculate the grid thickness h, grid angle C, grid volume V. The plane distribution map of the grid quality coefficient Q is as shown in Figure 9 (a). When 0°<C<5°, V>0, 0<Q<15, the grid quality is considered good. As shown in Figure 9 (b), after quality control, the number of grids with good grid quality is higher than 95% of the total number, and the grid quality is considered good.

[0140] Step 5: Control the quality of the facies model.

[0141] First, analyze the distribution trend of sedimentary facies. For the B layer of the oil reservoir, there are three sedimentary trends of upper, middle and lower in this layer section. Check whether the facies model at different vertical positions is consistent with the trend map used in sedimentary facies modeling respectively. Figure 10The sedimentary facies trend of the middle B layer of the reservoir is shown in the following table. Figure 10 b) and the trend used in sedimentary facies modeling (e.g. Figure 10 The sedimentary facies distribution histogram of reservoir B layer was drawn. The results showed that the sedimentary facies distribution of logging data, model coarsening data and model data matched well, and it was considered that the quality of the facies model was good (as shown in Figure 2). Figure 11 shown).

[0142] Step 6: Perform quality control on the reservoir parameter model;

[0143] Draw the plane distribution map of porosity and permeability for each layer and each sedimentary phase, and analyze the distribution pattern. Figure 12 The average porosity and average permeability distribution diagram of sedimentary phase I in layer B is shown in Figure 1. Figure 12 As shown, the results show that the overall porosity of the sedimentary facies (such as Figure 12 (a)), permeability (as shown in Figure 12 (b) is higher, which is the main reservoir. At the same time, the value in the northeast direction of the work area is higher, and the value in the southwest direction is lower, which reflects the regularity and is consistent with the geological understanding. It is believed that the plane distribution is relatively reasonable.

[0144] Then the porosity of each interval and each sedimentary phase (such as Figure 13 (a)), permeability (as shown in Figure 13 (b) shows the distribution histogram. The results show that when the well logging data, model coarsening data and model data in the distribution histogram match well (such as Figure 13 The maximum, minimum and average values ​​of each layer segment and each sedimentary facies attribute are similar (see Tables 1 and 2), and it is believed that the reservoir parameter model has good quality.

[0145] Table 1 Statistics of porosity values ​​of sedimentary facies I in reservoir B layer

[0146] project Minimum Maximum average value Standard deviation Data in reservoir parameter model 0.07 0.14 0.1 0.02 Coarsening data 0.07 0.14 0.11 0.02 Well logging curve 0.05 0.16 0.1 0.02

[0147] Table 2 Permeability statistics of sedimentary phase I in reservoir B layer (unit: mD)

[0148] project Minimum Maximum average value Standard deviation Data in reservoir parameter model 0.3 5.26 2.18 1.49 Coarsening data 0.37 5.26 2.3 1.49 Well logging curve 0.32 5.36 2.09 1.68

[0149] Step 7: Perform comprehensive quality control on the facies model and reservoir parameter model.

[0150] Draw the porosity and permeability cross-plots of different sedimentary phases by layer. Figure 14 is the cross-plot of porosity and permeability of different sedimentary phases in reservoir B layer. Figure 14 (a) is the cross plot of porosity and permeability of different sedimentary phases in the well logging curve. Figure 14(b) is the cross-plot of porosity and permeability of different sedimentary phases in the 3D geological model. Figure 14 (a) and 14(b), the results show that the crossplot of porosity and permeability in the logging curve is similar to the distribution characteristics of the crossplot in the phase model, the new porosity model, and the permeability model, and it is believed that the phase model and the reservoir parameter model are more reliable.

[0151] Step 8: performing quality control on the new saturation model;

[0152] like Figure 15 As shown in the figure, for the location of the single well before the start of oil production or injection, the saturation value in the new saturation model is close to the saturation value interpreted by well logging, indicating that the new saturation model is of high quality.

[0153] Step 9: Perform quality control on the reserve calculation results.

[0154] The results show that the reserve calculation results of the new 3D geological model are significantly higher than the original reserve calculation results of the old 3D geological model (i.e. the previous version of the 3D geological model. The new 3D geological model is obtained by improving the old 3D geological model). The reserve calculation results of the previous version are studied and the numerical differences in different aspects are analyzed. The differences between the new and old structural maps are analyzed and the difference maps between the new and old structures are drawn (such as Figure 16 As shown in Table 3, it can be seen that the difference between the new and old 3D geological models in terms of structure is small. The difference in free water interface and oil-bearing area between the new and old 3D geological models is statistically analyzed (see Table 3). It can be seen that the oil-water interface of the new 3D geological model is significantly lower than that of the old 3D geological model, while the oil-bearing area is significantly higher than that of the old 3D geological model. The porosity distribution histogram of the model is drawn to analyze the new porosity model (such as Figure 17 (a)) and the old porosity model (as shown in Figure 17 (b) Porosity distribution difference (as shown in Figure 17 As shown in the figure), it can be seen that the porosity values ​​in the new porosity model are generally higher than those in the old porosity model; the saturation distribution histogram of the model is drawn to analyze the distribution differences between the new saturation model and the old saturation model (as shown in the figure). Figure 18 As shown), the new saturation model (as shown Figure 18 (a)) is generally lower than the old saturation model (such as Figure 18 (b)). Overall, the model quality is high, the reasons for the changes in geological reserves are clear, and the 3D geological model and reserve calculation results are reliable.

[0155] Table 3 Differences in free water interface and oil-bearing area between the new and old 3D geological models of reservoir B layer

[0156] project New 3D geological model Old 3D geological model From oil-water interface 3360m 3310m Oil-bearing area <![CDATA[287km 2 ]]> <![CDATA[225km 2 ]]>

[0157] Based on the above-mentioned method for controlling the quality of a three-dimensional geological model, the present invention further proposes a device for controlling the quality of a three-dimensional geological model, comprising:

[0158] Fault model unit, used to perform quality control on the fault model in the tectonic framework model;

[0159] Level model unit, used to perform quality control on level models in the construction framework model;

[0160] Grid model unit, used to perform quality control on the grid model in the construction framework model;

[0161] Phase model unit, used for quality control of phase models;

[0162] Reservoir parameter model unit, used for quality control of reservoir parameter model;

[0163] Comprehensive unit for comprehensive quality control of facies model and reservoir parameter model;

[0164] A new saturation model unit, used for quality control of the new saturation model;

[0165] The reserve calculation unit is used to perform quality control on the reserve calculation results obtained based on the three-dimensional geological model.

[0166] Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for quality control of a three-dimensional geological model, characterized in that: Including: Perform quality control on the fault model in the structural framework model; Perform quality control on the bedding model in the structural framework model; Perform quality control on the grid model in the structural framework model; Perform quality control on the facies model; Perform quality control on the reservoir parameter model; Perform comprehensive quality control on the facies model and the reservoir parameter model; Perform quality control on the new saturation model; Perform quality control on the reserve calculation results obtained based on the three-dimensional geological model.

2. The method for quality control of a three-dimensional geological model according to claim 1, characterized in that: The specific steps for performing quality control on the fault model in the structural framework model are as follows: Analyze the fault properties; Draw the throw distribution diagram of each fault, and judge whether the throw at the fault edge of each fault is less than or equal to the throw in the middle of the fault; judge whether the throw value in the fault model conforms to the fault distance of the seismic event or the throw value confirmed by well logging data; if both are yes, the fault model has good quality.

3. The method for quality control of a three-dimensional geological model according to claim 1, characterized in that: The specific steps for performing quality control on the bedding model in the structural framework model are as follows: Judge whether there is a phenomenon of altitude change in the bedding model; If so, determine the altitude change coefficient H of the bedding model; When H < 5, the grid quality of the bedding model is good; when 5 < H < l0, the grid quality of the bedding model is average; when H > 10, the grid quality of the bedding model is poor; The altitude change coefficient is determined by the following formula: Among them, D i D is the altitude of the i-th grid whose perimeter distance is within the first threshold; a is the geometric mean of the altitudes of all grids whose perimeter distance to the calculated grid is within the first threshold; n is the number of grids whose perimeter distance to the calculated grid is within the first threshold; D c is the grid width.

4. The method for quality control of a three-dimensional geological model according to claim 3, characterized in that: The quality control on the bedding model in the structural framework model further includes the following steps: Draw the histogram of the small layer thickness, and analyze whether the thickness distribution conforms to the geological understanding; Draw the stratigraphic thickness map of each small layer, observe whether the stratigraphic thickness change conforms to the structural style and sedimentary environment, and judge whether there is a change within the set range of the stratigraphic thickness; If so, determine the reservoir thickness change coefficient M; When M > 0.7, it is considered that the stratigraphic thickness changes rapidly; The reservoir thickness change coefficient M is determined by the following formula: Among them, A i A is the reservoir thickness value of the i-th grid whose perimeter distance is within the first threshold; a is the geometric mean of the reservoir thickness values ​​of all grids whose periphery distance of the calculated grid is within the first threshold; n is the number of grids whose periphery distance of the calculated grid is within the first threshold.

5. The method for quality control of a three-dimensional geological model according to claim 1, characterized in that: The specific steps for performing quality control on the grid model in the structural framework model are as follows: Judge the quality of a single grid in the grid model; When the thickness h of a single grid > 0.5m, the volume V > 0, and the angle 0° < C < 5°, the grid quality is considered good; Or When the volume V of a single grid > 0, 0 < Q < 15, the grid quality is considered good; where, the grid quality coefficient Q = C / h.

6. The method for quality control of a three-dimensional geological model according to claim 1, characterized in that: The specific steps for performing quality control on the facies model are as follows: When the sedimentary facies trend is the same within a single layer segment, check whether the sedimentary facies trend map in the facies model is consistent with the trend map used in sedimentary facies modeling; if it is consistent, the facies model has good quality; When different sedimentary trends appear within a single layer segment, check whether the facies models at different vertical positions are consistent with the trend map used in sedimentary facies modeling respectively; if they are consistent, the facies model has good quality; Draw the histogram of the sedimentary facies distribution. When the trend is not used to control the facies model, if the well logging data, the model coarsening data, and the facies data in the facies model match each other, the facies model is considered to have good quality.

7. The method for quality control of a three-dimensional geological model according to claim 1, characterized in that: The specific steps for performing quality control on the reservoir parameter model are as follows: Draw the plane distribution maps of porosity and permeability for each layer segment and each sedimentary facies. The changes in porosity and permeability in the plane distribution maps should conform to the geological understanding; Draw a distribution histogram of porosity and permeability for each layer segment and each sedimentary facies; when the well logging data, model coarsening data and data in the reservoir parameter model match in the distribution histogram, and the maximum, minimum and average values ​​of the attributes of each layer segment and each sedimentary facies match, the reservoir parameter model is considered to be of good quality.

8. The method for quality control of a three-dimensional geological model according to claim 1, characterized in that: The specific steps of performing comprehensive quality control on the facies model and the reservoir parameter model are as follows: Draw the porosity and permeability crossplots of different sedimentary facies. The porosity and permeability crossplots of different sedimentary facies in the porosity model and permeability model should match the porosity and permeability crossplot characteristics of different sedimentary facies in the logging curve.

9. The method for quality control of a three-dimensional geological model according to claim 1, characterized in that: The specific steps of quality control of the new saturation model are as follows: For individual well locations before production or injection begins in the reservoir, the saturation values ​​in the new saturation model should match the saturation values ​​interpreted from the well logs.

10. The method for quality control of a three-dimensional geological model according to claim 1, characterized in that: The specific steps of performing quality control on the reserve calculation results obtained based on the three-dimensional geological model are as follows: Analyze whether there are any differences between the reserve calculation results and the original reserve calculation results. If there are any differences, analyze the differences between the new and old structural maps, the differences in free water interfaces, and the differences in oil-bearing areas; Draw the porosity distribution histogram of the new porosity model and the old porosity model, and analyze the distribution difference between the new porosity model and the old porosity model; Draw the water saturation distribution histogram of the new saturation model and the old saturation model, and analyze the distribution difference between the new saturation model and the old saturation model.

11. A device for quality control of a three-dimensional geological model, characterized in that: include: Fault model unit, used to perform quality control on the fault model in the tectonic framework model; Level model unit, used to perform quality control on level models in the construction framework model; Grid model unit, used to perform quality control on the grid model in the construction framework model; Phase model unit, used for quality control of phase models; Reservoir parameter model unit, used for quality control of reservoir parameter model; Comprehensive unit for comprehensive quality control of facies model and reservoir parameter model; A new saturation model unit, used for quality control of the new saturation model; The reserve calculation unit is used to perform quality control on the reserve calculation results obtained based on the three-dimensional geological model.

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