Method for identifying CO2 drive gas channeling channel based on classified reservoir evaluation injection-production connectivity

Abstract

The invention belongs to the technical field of oil-gas field development, and discloses a method for identifying a CO2 drive gas channeling channel based on classified reservoir evaluation injection-production connectivity. The method comprises the following steps: determining a physical property lower limit by utilizing mercury injection data in coring well test analysis data, and establishing a physical property lower limit standard; the physical property lower limit standard corresponds to the logging curve characteristics, and a reservoir classification standard capable of popularizing the whole area is established; reservoir classification and discrimination of all wells in the whole area are completed; the injection-production connectivity is evaluated according to the classified reservoirs, and an injection-production connectivity evaluation standard is established; completing injection-production connectivity evaluation on all well groups in the whole area; and according to the gas channeling well injection-production connectivity evaluation result, the gas channeling channel is recognized, and the recognition result is verified through monitoring data. According to the method, the test analysis data of the cored well is fully utilized and combined with the logging curve data, the reservoir classification standard is established, the injection-production connectivity is evaluated by combining the reservoir classification result, then the gas channeling channel is identified, the method can be used as a strong theoretical basis for guiding plugging of the gas channeling layer, and the CO2 flooding development effect is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of oil and gas field development, and particularly relates to a method for identifying CO2 drive gas channeling channels based on classified reservoir evaluation injection-production connectivity. BACKGROUND

[0002] Carbon capture, utilization and storage (CCUS) is undoubtedly a practical move to win time for large-scale energy conservation and emission reduction and green low-carbon transformation as a key way for clean and low-carbon application of fossil energy. Among them, CO2 flooding enhanced oil recovery and storage technology is an important embodiment of utilization, which is currently in the key stage from pilot test to industrial test. However, due to the complexity of the development layer series of oil and gas fields, the plane contradiction and interlayer contradiction are prominent, and gas channeling inevitably occurs during CO2 flooding.

[0003] The gas channeling that occurs during CO2 flooding directly increases the cost of separating and reinjecting the produced gas and the difficulty of future storage. At present, most of the mines cannot accurately identify the gas channeling channels, and can only generally control the CO2 output by increasing or decreasing the injection amount at the injection end, with little effect.

[0004] In summary, how to identify the gas channeling channel and effectively control the gas channeling to increase the sweep volume and oil displacement efficiency of CO2, improve the recovery of oil and gas fields, and ensure the production capacity of the mine has become a problem to be solved. SUMMARY

[0005] The present application overcomes the problem that the gas channeling channel cannot be accurately identified during the CO2 flooding process, and effectively controls the gas channeling. A method for identifying CO2 drive gas channeling channels based on classified reservoir evaluation injection-production connectivity is provided, which provides a basis for identifying and plugging the gas channeling channel in the mine, so as to increase the sweep volume and oil displacement efficiency of injected CO2 in the underground, and greatly improve the recovery.

[0006] The technical problem solved by the present application can be realized by using the following technical scheme:

[0007] A method for identifying CO2 drive gas channeling channels based on classified reservoir evaluation injection-production connectivity, comprising the following steps:

[0008] S1: determining the physical property lower limit by using the mercury injection data in the coring well test analysis data, and establishing a physical property lower limit standard;

[0009] S2: corresponding the physical property lower limit standard with the logging curve characteristics, and establishing a reservoir classification standard that can be extended to the whole area;

[0010] S3: completing the reservoir classification discrimination of all wells in the whole area;

[0011] S4: According to the classified reservoir evaluation injection-production connectivity, the injection-production connectivity evaluation standard is established;

[0012] S5: The injection-production connectivity evaluation of all well groups in the whole region is completed;

[0013] S6: According to the injection-production connectivity evaluation result of the gas channeling well, the gas channeling channel is identified, and the monitoring data is used to verify the identification result.

[0014] In S1, the mercury injection data in the test analysis data of the coring well in the research area (note: if there is no coring well in the research area, the nearest coring well data can be selected) is used to draw the drainage pressure and porosity intersection graph, the average pore radius and porosity intersection graph, and the permeability and average pore radius intersection graph, and the physical property lower limit of the research area is determined, and on this basis, the reservoir classification standard suitable for the research area is summarized and refined.

[0015] In S2, the reservoir classification standard established in S1 is corresponded with the curve characteristics in the logging data, the quantification is realized, and the reservoir classification standard which can be applied in the whole region is established.

[0016] In S3, the reservoir classification standard which can be applied in the whole region established in S2 is used to complete the reservoir classification identification of all wells in the whole region.

[0017] In S4, the injection-production connectivity is evaluated according to the reservoir classification identification result of all wells in the whole region in S3, and the injection-production connectivity evaluation standard is established.

[0018] In S5, according to the injection-production connectivity evaluation standard established in S4, the injection-production connectivity evaluation of all well groups in the whole region is completed, and the well group connectivity grid chart is drawn with the oil production well (or injection well) as the center.

[0019] In S6, the well group where the gas channeling well is located is found in the well group connectivity grid chart drawn in S5, the gas channeling channel is effectively identified in combination with the injection-production connectivity evaluation result, the gas channeling channel identified in S6 is verified by using the water (gas) profile and tracer monitoring data, and whether the standard which can be applied to identify the gas channeling channel of all gas channeling wells in the region is reached is judged, so as to provide a basis for the next step of plugging the gas channeling layer. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly explain the technical scheme of the present application, the drawings needed in the explanation process will be briefly introduced below. Obviously, the drawings introduced below are only part of the examples of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0021] Figure 1 It is a flowchart of the method of the present application;

[0022] Figure 2 The mercury saturation vs. capillary pressure crossplot for qn1 formation;

[0023] In Fig. 3, Figure 3a The displacement pressure vs. porosity crossplot; Figure 3b The mean pore radius vs. porosity crossplot; Figure 3c The permeability vs. mean pore radius crossplot;

[0024] Figure 4a-1 The mercury injection and expulsion saturation vs. capillary pressure crossplot for core No. S1 of well H75, Figure 4a-2 The well logging interpretation result corresponding to core No. S1 of well H75; Figure 4b-1 The mercury injection and expulsion saturation vs. capillary pressure crossplot for core No. S11 of well H104, Figure 4b-2 The well logging interpretation result corresponding to core No. S11 of well H104; Figure 4c-1 The mercury injection and expulsion saturation vs. capillary pressure crossplot for core No. S3 of well H104, Figure 4c-2 The well logging interpretation result corresponding to core No. S3 of well H104; Figure 4d-1 The mercury injection and expulsion saturation vs. capillary pressure crossplot for core No. S3 of well H57, Figure 4d-2 The well logging interpretation result corresponding to core No. S3 of well H57;

[0025] Figure 5 The reservoir classification interpretation result for well H79-10-10;

[0026] Figure 6 The grid chart of the communication between well H79-2-6 and adjacent injection wells;

[0027] Figure 7 The comparison chart of the third water absorption profile logging interpretation of well H+79-2-4;

[0028] Figure 8 The schematic diagram of the tracer migration speed and concentration of well H+79-2-4.

[0029] Compared with the prior art, the present application has the beneficial effects as follows:

[0030] In view of the problem that gas channeling inevitably occurs in the CO2 oil displacement process but the gas channeling channel cannot be effectively identified and controlled, the present application fully utilizes the assay analysis data of coring wells, combines with well logging curve data, establishes a reservoir classification standard, further combines with the reservoir classification result to evaluate the injection-production communication, and then identifies the gas channeling channel, which can be used as a strong theoretical basis for guiding the plugging of the gas channeling layer and improving the CO2 displacement development effect. DETAILED DESCRIPTION

[0031] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0032] Embodiment 1

[0033] The technical solutions of the method for identifying CO2 flooding gas channeling based on classified reservoir evaluation of injection-production connectivity provided by the embodiments of the present application will be described in detail below through specific embodiments of H125 area in Jilin Oilfield. H125 area in Jilin Oilfield started to apply CO2 flooding development in August 2020, which is the first industrial demonstration block in Jilin Oilfield, and a five-point infilling well pattern is applied for multi-layer development. Due to the complexity of the development layer system, the interlayer and plane contradictions are prominent, and gas channeling occurs in some wells. However, due to multi-layer production, the gas channeling channel cannot be accurately determined, which greatly affects the development effect.

[0034] As shown in Figure 1 , a method for identifying CO2 flooding gas channeling based on classified reservoir evaluation of injection-production connectivity comprises the following steps:

[0035] S1: determining the physical property lower limit by using the mercury injection data in the coring well test analysis data, and establishing a physical property lower limit standard;

[0036] The mercury injection experiment provides a series of pore structure parameters, which reflect the physical property lower limit of the reservoir from different aspects. Since there is no cored well drilled in H125 area, the data of 16 core samples from 5 wells in the gas adjacent area are applied to establish the mercury injection saturation and capillary pressure cross plot of qn1 formation (see Figure 2 ). As can be seen from the figure, the core samples marked as type I (red), type II (blue) and type III (brown) in the figure have different displacement pressures, but their flat sections are not very long, indicating that the pore distribution is not very concentrated, and the pore structure is complex; the core sample of type IV (black) has a longer flat section, indicating that the pore distribution is relatively concentrated, but the displacement pressure is large, indicating that the pore is small and the porosity and permeability conditions are poor.

[0037] The core data is used to draw the displacement pressure and porosity cross plot ( Figure 3a ), the average pore radius and porosity cross plot ( Figure 3b ), and the permeability and average pore radius cross plot ( Figure 3c ). Figure 3a It is indicated that the higher the porosity is, the lower the displacement pressure is, Figure 3b , 3c It is indicated that the larger the pore radius is, the larger the porosity and permeability are.

[0038] Thus, the lower limit of physical properties and the reservoir classification criteria can be determined by cross plot. The lower limit of physical properties in the block is: porosity < 6%, permeability < 0.07 mD, drainage pressure > 1 MPa, and average pore radius < 0.2 μm. The qn1 reservoir in the study area is divided into four categories, and the classification criteria of each category are shown in Table 1.

[0039] Table 1 Classification criteria of qn1 reservoir

[0040] Classification Porosity (%) Permeability (mD) Displacement pressure (MPa) Mean pore radius (μm) Class I ≥14 ≥5 ≤0.21 ≥1.4 Class II ≥10 ≥1 ≤0.35 ≥0.6 Class III ≥6 ≥0.07 ≤1 ≥0.2 Class IV <6 <0.07 >1 <0.2

[0041] S2: Correspond the lower limit of physical properties to the logging curve characteristics to establish the reservoir classification criteria which can be applied to the whole area;

[0042] Correspond the reservoir classification criteria established in S1 to the curve characteristics in logging data to realize quantification, and establish the reservoir classification criteria which can be applied to the whole area. The specific classification and logging curve characteristics are summarized as follows:

[0043] Class I reservoir: The S1 core of H75 well has a porosity of 16.3% and a permeability of 11.88 mD. The pore radius is large with an average of 1.435 μm, the throat width is large with a value of 10.19 μm, and the drainage pressure is low with a value of 0.138 MPa (see Figure 4a-1 ). The logging curve depth corresponding to the S1 core is about 2349.4 meters (see Figure 4a-2 ), and the acoustic time at this depth is 245 μs / m, the natural gamma is 78 API, the porosity is 15.8%, and the permeability is 12.03 mD.

[0044] Class II reservoir: The S11 core of H104 well has a porosity of 12.5% and a permeability of 4.92 mD. The average pore radius is 1.24 μm, the drainage pressure is low with a value of 0.21 MPa (see Figure 4b-1 ), and the throat width is 10.34 μm. The logging curve depth corresponding to the S11 core is about 2435.4 meters (see Figure 4b-2 ), and the acoustic time at this depth is 225.2 μs / m, the natural gamma is 76 API, the porosity is 11.35%, and the permeability is 2.62 mD.

[0045] Class III reservoir: The S3 core of H104 well has a porosity of 6.7% and a permeability of 0.16 mD. The pore radius is small with an average of 0.468 μm, the throat width is small with a value of 3.7 μm, and the drainage pressure is 0.48 MPa (see Figure 4c-1 ). The logging curve depth corresponding to the S3 core is about 2369 meters (see Figure 4c-2 ), and the acoustic time at this depth is 208 μs / m, the natural gamma is 76 API, the porosity is 7.8%, and the permeability is 0.45 mD.

[0046] Class IV reservoir: core S3 of well H57, with a porosity of 6.2%, a permeability of 0.03 mD, a small pore radius with an average value of 0.056 μm, and a high displacement pressure of 5.74 MPa (see Figure 4d-1 The depth of the well logging curve corresponding to the core S3 of Well H57 is about 2338 meters (see Figure 4d-2 ), the corresponding acoustic wave time difference at this depth is 208μs / m, the natural gamma is 76API, the porosity is 7.8%, and the permeability is 0.45mD.

[0047] By mapping the reservoir property classification criteria to well logging characteristics, we can see that as reservoir type deteriorates from good to poor, the reservoir porosity, permeability, mean pore radius, and duct width decrease, while the displacement pressure increases. Based on a combination of core analysis, mercury injection data, and well logging data, the final reservoir classification criteria for the QN1 formation are presented (see Table 2).

[0048] Table 2 Reservoir classification standards

[0049]

[0050] S3: Complete reservoir classification and identification for all wells in the area;

[0051] The reservoir classification standard established in S2, which can be generalized for the entire region, was used to classify all wells in the region. The reservoir types of the 16 sublayers of the qn1 formation in 70 wells in the study area were divided. Figure 5 This is the interpretation result map of the reservoir classification of H79-10-10 well based on the reservoir classification standard among 70 wells.

[0052] S4: Evaluate injection-production connectivity based on classified reservoirs and establish injection-production connectivity evaluation standards;

[0053] Based on the reservoir classification results for all wells in the area in S3, injection-production connectivity was evaluated and a standard for injection-production connectivity was established. Oil and water well connectivity is positively correlated with reservoir porosity and permeability, meaning connectivity is related to reservoir type. Therefore, interwell connectivity can be categorized based on reservoir characteristics, with connectivity being classified as good, relatively good, fair, and poor. Class I reservoirs have better connectivity with other Class I reservoirs than with other Class I reservoirs, while Class IV reservoirs have the worst connectivity with other Class IV reservoirs. Specific connectivity classification standards are shown in Table 3.

[0054] Table 3 Reservoir classification standards

[0055]

[0056] S5: Complete injection-production connectivity evaluation for all well groups in the area;

[0057] According to the evaluation standard of injection-production connectivity established in S4, 39 small layer classification connectivity tables with oil well as the center are established, and 39 connectivity grid diagrams are drawn. Take H79-2-6 well as an example for illustration. First, according to the reservoir classification standard, the single well reservoir classification and the thickness table of class I to class IV reservoirs are formed (the reservoir classification column in the table is colored, which indicates that the layer is a perforated layer, and different colors represent different reservoir types). Then, the oil well and its adjacent water wells are placed in the same table, and the connectivity is divided according to the reservoir classification of the oil and water wells in the same small layer. The connectivity is color-coded, with bright yellow representing good connectivity, orange representing better connectivity, light blue representing general connectivity, and dark blue representing poor connectivity (see Table 4). Then, the connectivity grid diagram is drawn with the oil well as the center. The colors of the connected small layers in the connectivity grid diagram are consistent with those in the connectivity table (see Figure 6 ).

[0058] Table 4 Small layer classification connectivity table of H79-2-6 well and adjacent injection wells

[0059]

[0060] S6: According to the evaluation results of injection-production connectivity of gas channeling wells, identify gas channeling channels, and verify the identification results by monitoring data.

[0061] In S5, the connectivity grid diagram of all well groups is found in the well group where the gas channeling well is located. Taking gas channeling well H79-2-6 well as an example, combined with the evaluation results of injection-production connectivity, the gas channeling channels are effectively identified. The identified gas channeling channels are verified by water (gas) absorption profile and tracer monitoring data, to determine whether they meet the standard of being applicable to identifying gas channeling channels of all gas channeling wells in the area, and to provide a basis for the next step of plugging gas channeling layers.

[0062] From the connectivity table (see Table 4) and the grid diagram (see Figure 6 ), it can be seen that H79-2-6 well is well connected with H+79-2-4 well 7, 12 small layers, well connected with H+79-4-4 well 12 small layers, well connected with H+79-2-2 well 7, 12 small layers, and the thickness of class I reservoir of 12 small layers in the above four wells is more than two meters. Therefore, it is judged that the 12th small layer is a gas channeling channel.

[0063] The identified gas channeling channels are verified by water (gas) absorption profile and tracer monitoring data, to determine whether they meet the standard of being applicable to identifying gas channeling channels of all gas channeling wells in the area, and to provide a basis for the next step of plugging gas channeling layers.

[0064] H+79-2-4 well was dynamically monitored by water absorption profile for three times in June 2021, June 2022 and November 2022 (see Figure 7), reflecting that the water absorbing layer is in 5, 7, 8, 11, 12 small layers, wherein the 12 small layer is the main water absorbing layer. The water absorbing profile logging shows that the water absorbing amount of the 12 small layer accounts for 47.48% of the total well injection amount in June 2021, and accounts for 49.59% and 65.95% of the total well injection amount in June and November 2022 respectively, and at the same time, from the analysis of the reservoir physical property and the thickness of the I to II type reservoir, the 12 small layer is the best. It is shown that with the prolongation of the displacement time, the profile balance becomes poor, and the fluid rushes along the high permeability strip, and the water absorbing amount of the 12 small layer of the H+79-2-4 well is consistent with the connectivity of the H79-2-6 well.

[0065] The tracer monitoring data carried out in the H+79-2-4 well shows (see Figure 8 ), after the H+79-2-4 well is put into the tracer, the tracer is found in the surrounding four oil wells H79-4-4, H79-2-6, H79-4-06 and H79-2-4, and the tracer is found fastest and the amount of the tracer is the most in the H79-2-6 well. This is because the I type reservoir of the H79-2-6 well is 3.4 meters, the II type reservoir is 3.8 meters, the thickness of the I and II type reservoirs is the largest, and the well group connectivity analysis is consistent with the tracer monitoring situation. The connectivity of the H+79-2-4 well and the H79-2-6 well is the best, the injection is the fastest, and the H79-2-6 well is most affected by the water injection (gas injection) of the H+79-2-4 well.

[0066] Therefore, if the gas channeling channel of the H79-2-6 well is blocked subsequently, the 12 layer of the H+79-2-4 well can be blocked.

[0067] The present application deeply utilizes the existing data in the mining area, and effectively identifies the gas channeling channel without increasing any cost, thereby providing a basis for subsequent plugging of the gas channeling layer, further expanding the gas swept volume, improving the CO2 flooding development effect, filling the blank of application of CO2 flooding in the gas channeling control, solving the problem of insufficient experience of CO2 as a new emerging hot oil displacement medium to a certain extent, and providing a new idea for subsequent application of CO2 flooding in oil fields.

[0068] The method for identifying the CO2 flooding gas channeling channel based on the classification reservoir evaluation injection-production connectivity is not limited to the above embodiments, and the technical solutions of each embodiment can be combined with each other, but it must be based on that the ordinary skilled in the art can realize, when the combination of the technical solutions appears mutual contradiction or cannot be realized, it should be considered that the combination of the technical solutions does not exist, and is not within the protection scope required by the present application.

Claims

1. A method for identifying CO2 drive gas channeling pathways based on categorical reservoir evaluation of injection-production connectivity, characterized in that, The method comprises the following steps: S1: Determine the lower limit of physical property by using the mercury injection data in the coring well analysis data, and establish the lower limit standard of physical property; S2: Correspond the lower limit standard of physical property with the logging curve characteristics, and establish the reservoir classification standard which can be popularized in the whole region; S3: Complete the reservoir classification discrimination for all wells in the whole region; S4: Evaluate the injection-production connectivity according to the classified reservoir, and establish the evaluation standard of injection-production connectivity; S5: Complete the injection-production connectivity evaluation for all well groups in the whole region; S6: Identify the gas channeling channel according to the evaluation result of injection-production connectivity of gas channeling well, and verify the identification result by using the monitoring data.

2. The method of claim 1, wherein the CO2 flood channel is identified by In S1, if there is no coring well in the research area, select the nearest coring well data in the mining area.

3. The method of claim 1, wherein the method is used to identify CO2 flood gas channeling pathways based on categorical reservoir evaluation of injection-production connectivity. The specific method of S1 is: draw the intersection graph of displacement pressure and porosity, the intersection graph of mean pore radius and porosity, and the intersection graph of permeability and mean pore radius by using the mercury injection data in the coring well analysis data in the research area, and determine the lower limit of physical property in the research area, and then summarize and extract the standard suitable for the reservoir classification of the research area.

4. The method for identifying CO2 flooding channel based on the injection-production connectivity of the classified reservoir evaluation according to claim 1, characterized in that S2 The reservoir classification standard obtained by the logging curve characteristics is shown in the following table:

5. The method of claim 1, wherein the method is used to identify CO2 flood gas channeling pathways based on categorical reservoir evaluation of injection-production connectivity. In S3, the reservoir classification discrimination for all wells in the whole region is completed by using the reservoir classification standard which can be popularized in the whole region established in S2, and the reservoir categories of 16 small layers of qn1 formation in the well in the research area are divided.

6. The method of claim 1, wherein the method is used to identify CO2 flood gas channeling pathways based on categorical reservoir evaluation of injection-production connectivity. The injection-production connectivity evaluation standard in S4 is as follows:

7. The method of claim 1, wherein the method further comprises, In S5, according to the injection-production connectivity evaluation standard established in S4, the injection-production connectivity evaluation for all well groups in the whole region is completed, and the well group connectivity grid chart is drawn with the production well or the injection well as the center.

8. The method of claim 1, wherein the CO2 flood channel is identified by evaluating the injection-production connectivity based on the categorical reservoir evaluation. In S6, the well group where the gas channeling well is located is found by using all the well group connectivity grid charts drawn in S5, the gas channeling channel is effectively identified by combining the injection-production connectivity evaluation result, the monitoring data such as water absorption profile or gas absorption profile and tracer is used to verify the gas channeling channel identified in S6, and whether the standard of being popularized and applied to the gas channeling channel discrimination of all gas channeling wells in the region is reached is judged, and the basis for the next step of plugging the gas channeling layer is provided.

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