Method and device for identifying and predicting dominant flow channels in highly heterogeneous reservoirs

Abstract

This specification relates to the technical field of oil and gas development, and provides a method and device for identifying and predicting dominant flow channels for injection and flooding in highly heterogeneous oil reservoirs. The method includes: obtaining injection water samples and produced water samples corresponding to the target well; determining the ion composition corresponding to the injection water samples and produced water samples; calculating the salinity of the injection water sample and the salinity of the produced water sample based on the ion composition using a preset classification standard; analyzing the correlation between the salinity of the injection water sample and the salinity of the produced water sample at different sampling times, so as to obtain the corresponding dominant flow channel based on the correlation. Through the embodiments of this specification, the stability, identification and prediction accuracy, and cost of the identification and prediction of dominant flow channels for injection and flooding in highly heterogeneous oil reservoirs can be taken into account.

Description

Technical Field

[0001] This specification relates to the technical field of oil and gas development, and in particular to a method and device for identifying and predicting dominant injection and flooding flow channels in highly heterogeneous oil reservoirs. Background Art

[0002] Oilfield types are complex and diverse, with most reservoirs being continental deposits. These reservoirs have relatively weak natural energy and low recovery rates from depletion development. Consequently, most reservoirs utilize flooding, which involves injecting various media to replenish formation energy and thereby enhance recovery. However, due to the strong heterogeneity of continental sedimentary reservoirs, much of the flooding media circulates ineffectively along the dominant flow pathways, resulting in significant economic losses and reduced utilization of oil and gas resources in low-permeability layers, severely restricting efficient oilfield development.

[0003] Existing methods for identifying and predicting dominant flow paths include dynamic injection and production methods, interference well testing, gas chromatography, tracer testing, and mathematical comparison methods. However, each of these methods presents challenges, making it difficult to strike a balance between stability, identification and prediction accuracy, and cost. Dynamic injection and production methods suffer from poor stability and are easily affected by other factors. Well testing methods can affect normal reservoir production. Tracer testing is expensive, chromatography methods are labor-intensive, and resistivity curve comparison methods take a long time to identify. Therefore, a method for identifying and predicting dominant flow paths during flooding in highly heterogeneous reservoirs is urgently needed that balances stability, identification and prediction accuracy, and cost. Summary of the Invention

[0004] Given that the current methods for identifying and predicting dominant seepage channels include injection-production dynamic method, interference well testing method, gas chromatography, tracer detection, mathematical comparison method, etc., however, these identification and prediction methods each have some problems and it is difficult to balance stability, identification and prediction accuracy and cost. The injection-production dynamic method has poor stability and is easily affected by other factors. The well testing method can affect the normal production of the reservoir. The tracer detection cost is high. The chromatography method has a large workload. The identification and prediction time of the resistivity curve comparison method is long. This scheme is proposed to overcome the above problems or at least partially solve the above problems.

[0005] On the one hand, some embodiments of this specification aim to provide a method for identifying and predicting dominant flow paths in highly heterogeneous oil reservoirs during flooding, the method comprising:

[0006] Obtain injection water samples and produced water samples corresponding to the target well;

[0007] Determining the ion composition of the injected water sample and the produced water sample;

[0008] Calculating the salinity of the injected water sample and the salinity of the produced water sample using a preset classification standard based on the ion composition;

[0009] The correlation between the salinity of the injected water sample and the salinity of the produced water sample at different sampling times is analyzed to obtain the corresponding dominant seepage channel according to the correlation.

[0010] Furthermore, the preset classification standard is the Sulin classification standard.

[0011] Furthermore, the salinity of the injected water sample and the salinity of the produced water sample are calculated based on the ion composition using a preset classification standard, including:

[0012] Cations and anions corresponding to the Sulin classification standard are selected from the ion composition, and the mineralization of the injected water sample and the mineralization of the produced water sample are calculated based on the selection results.

[0013] Furthermore, the correlation between the salinity of the injected water sample and the salinity of the produced water sample at different sampling times is analyzed to obtain the corresponding dominant seepage channel according to the correlation, including:

[0014] Calculate the ratio between the salinity of the injected water sample and the salinity of the produced water sample at different sampling times;

[0015] Determine whether the ratios at different sampling times exceed a preset threshold;

[0016] If the preset threshold is not exceeded, the injection medium does not flow along the dominant seepage channel;

[0017] If the preset threshold is exceeded, the injection medium will flow along the dominant seepage channel. Based on the occurrence of crossflow, the target well will be tested for the production profile to obtain the corresponding dominant seepage channel.

[0018] Furthermore, if the preset threshold is exceeded, the injection medium will flow along the dominant seepage channel, and according to the occurrence of the crossflow, the target well is tested for the production profile. After the corresponding dominant seepage channel is obtained, the method further includes:

[0019] The dominant seepage channel is blocked to ensure normal production of the target well.

[0020] Furthermore, the historical salinity of the injection water samples of the predicted well and the historical salinity of the produced water samples at different sampling times are obtained; wherein the predicted well and the target well are produced under the drive of the same injection well;

[0021] Calculate the historical ratios of the historical salinity of the injected water samples and the historical salinity of the produced water samples at different sampling times;

[0022] Establishing a fitting model using the historical ratio, and obtaining a predicted time for the appearance of a dominant seepage channel in the well to be predicted based on the fitting model;

[0023] Verifying the predicted time based on the historical ratio, crossflow occurrence of the target well, and production correlation between the target well and the well to be predicted;

[0024] If the verification fails, the parameters of the fitting model are adjusted until the predicted time verification passes, thereby obtaining a predicted time that meets the verification conditions.

[0025] On the other hand, some embodiments of this specification also provide a device for identifying and predicting dominant flow channels in highly heterogeneous oil reservoirs, the device comprising:

[0026] A receiving module is used to obtain injected water samples and produced water samples corresponding to the target well;

[0027] A determination module, configured to determine the ion composition corresponding to the injected water sample and the produced water sample;

[0028] a calculation module, configured to calculate the mineralization of the injected water sample and the mineralization of the produced water sample according to the ion composition and using a preset classification standard;

[0029] The analysis module is used to analyze the correlation between the salinity of the injected water sample and the salinity of the produced water sample at different sampling times, so as to obtain the corresponding dominant seepage channel according to the correlation.

[0030] On the other hand, some embodiments of this specification further provide a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the computer program executes instructions of the above method when executed by the processor.

[0031] On the other hand, some embodiments of this specification further provide a computer storage medium having a computer program stored thereon, wherein the computer program executes the instructions of the above method when executed by a processor of a computer device.

[0032] On the other hand, some embodiments of this specification further provide a computer program product, which includes a computer program. When the computer program is executed by a processor of a computer device, the computer program executes instructions of the above method.

[0033] Some embodiments of this specification provide one or more technical solutions that have at least the following technical effects:

[0034] The embodiments of this specification first automatically obtain the injection water sample and the produced water sample corresponding to the target well, and determine the ion composition information of the injection water sample and the produced water sample. On the basis of the obtained ion composition, the preset classification standard is used to calculate the mineralization of the injection water sample and the mineralization of the produced water sample, thereby automatically analyzing the correlation between the mineralization of the injection water sample and the mineralization of the produced water sample at different sampling times, so as to judge the dominant seepage channel of the injection and flooding of the strongly heterogeneous oil reservoir based on the correlation relationship, and obtain the corresponding dominant seepage channel, thereby taking into account the stability, recognition prediction accuracy and cost of the identification and prediction of the dominant seepage channel of the injection and flooding of the strongly heterogeneous oil reservoir.

[0035] The above description is only an overview of the technical solutions of some embodiments of this specification. In order to more clearly understand the technical means of some embodiments of this specification, they can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of some embodiments of this specification more obvious and easy to understand, the specific implementation methods of some embodiments of this specification are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate some embodiments of this specification or technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments described in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without inventive work. In the drawings:

[0037] Figure 1 A schematic diagram of an implementation system of a method for identifying and predicting dominant flow channels in highly heterogeneous oil reservoirs according to some embodiments of this specification is shown;

[0038] Figure 2 A flowchart showing a method for identifying and predicting dominant flow channels in highly heterogeneous oil reservoirs according to some embodiments of this specification is shown;

[0039] Figure 3 This is a schematic diagram of the steps for analyzing and obtaining the dominant percolation channel in some embodiments of this specification;

[0040] Figure 4 This is a schematic diagram of the steps for predicting a well to be predicted in some embodiments of this specification;

[0041] Figure 5 This is a schematic diagram of the well pattern distribution corresponding to the highly heterogeneous oil reservoir in some embodiments of this specification;

[0042] Figure 6 A bar graph showing the salinity of produced water and injected water versus absolute sampling time in some embodiments of this specification;

[0043] Figure 7 This is a schematic diagram of the test results of the liquid production profile in some embodiments of this specification;

[0044] Figure 8 This is a scatter plot diagram of the salinity ratio of produced water samples and injected water samples and the relative sampling time in some embodiments of this specification;

[0045] Figure 9 This is a schematic diagram of oil saturation distribution between wells P3 and P7 in 2020 in some embodiments of this specification;

[0046] Figure 10 This is a schematic diagram of the structure of a device for identifying and predicting dominant flow channels in highly heterogeneous oil reservoirs according to some embodiments of this specification;

[0047] Figure 11 This is a schematic diagram of the computer device structure provided in some embodiments of this specification.

[0048] [Description of Reference Numerals]

[0049] 101. Terminal;

[0050] 102. Server;

[0051] 1001, receiving module;

[0052] 1002. Determine module;

[0053] 1003. Calculation module;

[0054] 1004. Analysis module;

[0055] 1102. Computer equipment;

[0056] 1104, processor;

[0057] 1106. Memory;

[0058] 1108, driving mechanism;

[0059] 1110, input / output interface;

[0060] 1112. Input device;

[0061] 1114. Output device;

[0062] 1116. Presentation equipment;

[0063] 1118. Graphical User Interface;

[0064] 1120, network interface;

[0065] 1122, communication link;

[0066] 1124. Communication bus. DETAILED DESCRIPTION

[0067] To help those skilled in the art better understand the technical solutions in this specification, the following will provide a clear and complete description of the technical solutions in the embodiments of this specification, in conjunction with the accompanying drawings of some embodiments of this specification. Obviously, the embodiments described are only some of the embodiments of this specification, not all of them. All other embodiments obtained by those skilled in the art based on some of the embodiments in this specification without creative work should fall within the scope of protection of this specification.

[0068] It should be noted that the terms "first," "second," and the like in the specification and claims herein and in the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a particular order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or device comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to these processes, methods, products, or devices.

[0069] It should be noted that the acquisition, storage, use, and processing of data in the technical solution of this application comply with the relevant provisions of relevant laws and regulations.

[0070] It should be noted that in the embodiments of this specification, certain software, components, models and other existing solutions in the industry may be mentioned. They should be regarded as exemplary and their purpose is only to illustrate the feasibility of implementing the technical solution of this application, but it does not mean that the applicant has or will necessarily use the solution.

[0071] like Figure 1The system diagram for implementing the method for identifying and predicting dominant flow paths for flooding in highly heterogeneous reservoirs according to an embodiment of the present invention is shown. The system may include a terminal 101 and a server 102. Terminal 101 and server 102 communicate via a network, which may include a local area network (LAN), a wide area network (WAN), the Internet, or a combination thereof, and is connected to a website, user devices (e.g., computing devices), and back-end systems. A staff member may send a request for identifying and predicting dominant flow paths for flooding in highly heterogeneous reservoirs to server 102 via terminal 101. Upon receiving the request, server 102 retrieves data from a database for computational processing to obtain an identification and prediction result, and then sends the result to terminal 101, allowing the staff member to process the work based on the result.

[0072] In the embodiments of this specification, the server 102 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers. It can also be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDN, Content Delivery Network), and big data and artificial intelligence platforms.

[0073] In an optional embodiment, the terminal 101 may include, but is not limited to, electronic devices such as self-service terminals, desktop computers, tablet computers, laptop computers, and smart wearable devices. Optionally, the operating system running on the electronic device may include, but is not limited to, Android, iOS, Linux, and Windows. Of course, the terminal 101 is not limited to the aforementioned electronic devices having a certain physical form; it may also be software running on the aforementioned electronic devices.

[0074] In addition, it should be noted that Figure 1 What is shown is only an application environment provided by the present disclosure. In actual application, multiple terminals 101 may be included, and this specification does not limit this.

[0075] Figure 2This is a flow chart of the method for identifying and predicting the dominant flow channel of injection and flooding in a highly heterogeneous reservoir provided by an embodiment of the present invention. This specification provides the method operation steps described in the embodiment or flow chart, but may include more or fewer operation steps based on conventional or non-creative work. The order of steps listed in the embodiment is only one way of executing the steps among many, and does not represent the only execution order. When the actual system or device product is executed, it can be executed in the order or in parallel according to the method shown in the embodiment or the accompanying drawings. Specifically, Figure 2 As shown, applying the above-mentioned server side, the method may include:

[0076] S201: Obtaining injected water samples and produced water samples corresponding to the target well;

[0077] S202: Determine the ion composition of the injected water sample and the produced water sample;

[0078] S203: Calculating the mineralization of the injected water sample and the mineralization of the produced water sample according to the ion composition using a preset classification standard;

[0079] S204: Analyze the correlation between the salinity of the injected water sample and the salinity of the produced water sample at different sampling times, so as to obtain the corresponding dominant seepage channel according to the correlation.

[0080] The embodiments of this specification first automatically obtain the injection water sample and the produced water sample corresponding to the target well, and determine the ion composition information of the injection water sample and the produced water sample. On the basis of the obtained ion composition, the preset classification standard is used to calculate the mineralization of the injection water sample and the mineralization of the produced water sample, thereby automatically analyzing the correlation between the mineralization of the injection water sample and the mineralization of the produced water sample at different sampling times, so as to judge the dominant seepage channel of the injection and flooding of the strongly heterogeneous oil reservoir based on the correlation relationship, and obtain the corresponding dominant seepage channel, thereby taking into account the stability, recognition prediction accuracy and cost of the identification and prediction of the dominant seepage channel of the injection and flooding of the strongly heterogeneous oil reservoir.

[0081] It can be understood that in some embodiments, reservoirs can be developed through flooding, where different media are injected to replenish formation energy, thereby achieving enhanced oil recovery. However, due to the strong heterogeneity of continental sedimentary reservoirs, most of the flooding media circulates ineffectively along the dominant flow pathways, resulting in significant economic losses and reducing the utilization of oil and gas resources in low-permeability layers, thus severely restricting the efficient development of the oil field.

[0082] Specifically, in some embodiments, in the field of identification and prediction of dominant seepage channels, the on-site emphasis is placed on the study of crude oil testing data, mainly by qualitatively judging the dominant channel through the relationship between produced oil and produced water (water content), while ignoring the use of injection and production water data, and not conducting a source analysis of the produced water from production wells, that is, whether the produced water is mainly original formation water or water injected from injection wells during the development process.

[0083] In some embodiments, when obtaining the injection water sample and the produced water sample corresponding to the target well, the storage container needs to be rinsed at least 3 times with the water sample at the sampling point during sampling. At the same time, the water sample is filled to overflowing in the container during sampling and sealed for storage to reduce interference caused by the reaction of oxygen and carbon dioxide in the air and vibration interference during sample transportation. Generally, during the sampling and storage process, 500ml to 1000ml of sample can meet the needs of most physical and chemical analyses, and sometimes more large samples or multiple samples are required. At the same time, before sampling, it is also necessary to stick a label written with waterproof ink on the sampler. The sample label contains at least sample information, sampler, sampling point, analysis requirements, sampling conditions, sampling date and sampling time, so as to ensure that the information of the injection water sample and the produced water sample corresponding to the target well is accurate and effective.

[0084] Furthermore, in some embodiments, after obtaining the injected water sample and the produced water sample, it is necessary to determine the ion composition corresponding to the injected water sample and the produced water sample. Specifically, in some embodiments, Na + , K + , Ca 2+ Mg 2+ 、SO4 2- 、Cl - Ion determination can be carried out by ion chromatography; the ion concentration can be determined by analyzing the peak height and peak area of ​​the ion in the ion chromatogram and the corresponding standard working curve. 2- 、HCO3 - Anions can be determined using potentiometric titration. This method uses a glass electrode as the indicator electrode and a calomel electrode as the reference electrode. Titration is performed with an acid standard solution, and the endpoint is determined using a potentiometric titrator. 100 ml of a water sample is titrated with a hydrochloric acid standard solution. When the pH reaches 8.3, the first endpoint is reached. The amount of hydrochloric acid standard solution consumed is recorded. Continue titrating with the hydrochloric acid standard solution until the pH reaches 4.4-4.5, reaching the second endpoint. The amount of hydrochloric acid standard solution consumed is recorded. A titration curve is then plotted showing the pH value versus the amount of acid standard solution used during titration. The content of the corresponding component can then be calculated.

[0085] Furthermore, in some embodiments, for highly heterogeneous oil reservoirs, the preset classification standard is the Sulin classification standard. The Sulin classification method can link the chemical composition of groundwater with the natural environmental conditions in which it is located, and use different water types to represent different geological environments. It is suitable for the identification and prediction of dominant seepage channels in highly heterogeneous oil reservoirs.

[0086] Furthermore, in some embodiments, the salinity of the injected water sample and the salinity of the produced water sample are calculated based on the ion composition using a preset classification standard, including:

[0087] Cations and anions corresponding to the Sulin classification standard are selected from the ion composition, and the mineralization of the injected water sample and the mineralization of the produced water sample are calculated based on the selection results.

[0088] It can be understood that in some embodiments, the difference between the mineralization of the injected water sample and the mineralization of the produced water sample can be used to predict the dominant seepage channel, and the cations and anions based on the Sulin classification standard can accurately reflect the characteristics of the sample, ensuring the accuracy of the calculated mineralization of the injected water sample and the mineralization of the produced water sample.

[0089] Refer to the attached Figure 3 In some embodiments, analyzing the correlation between the salinity of the injected water sample and the salinity of the produced water sample at different sampling times to obtain the corresponding dominant seepage channel based on the correlation may include:

[0090] S301: Calculating the ratio between the salinity of the injected water sample and the salinity of the produced water sample at different sampling times;

[0091] S302: Determine whether the ratios at different sampling times exceed a preset threshold;

[0092] S303: If the preset threshold is not exceeded, the injection medium does not flow along the dominant seepage channel;

[0093] S304: If the preset threshold is exceeded, the injection medium will flow along the dominant seepage channel, and a production profile test will be performed on the target well according to the occurrence of the crossflow to obtain the corresponding dominant seepage channel.

[0094] It can be understood that in some embodiments, in typical embodiments, the sampling time can be in months to fully ensure the richness of the data. The unit of the sampling time is not specifically limited in this article. Then, the ratio between the salinity of the injected water sample and the salinity of the produced water sample at different sampling times is calculated. Whether the injection medium flows along the dominant seepage channel is determined based on whether the ratio exceeds a preset threshold. Specifically, the preset threshold is determined based on the geological characteristics of the highly heterogeneous reservoir. In some embodiments, the preset threshold The common value of is 0.85. If the difference between the salinity of the injected water sample and the salinity of the produced water sample is large, that is, the ratio of the salinities is less than 0.85, it means that the injection medium has not flowed along the dominant seepage channel. If the difference between the salinity of the injected water sample and the salinity of the produced water sample is small, that is, the ratio of the salinities is greater than 0.85, it means that the injection medium has flowed along the dominant seepage channel. At this time, it is necessary to conduct a production profile test on the target well according to the occurrence of crossflow to obtain the dominant seepage channel corresponding to the target well.

[0095] Furthermore, in some embodiments, if a preset threshold is exceeded, the injection medium will flow along the dominant seepage channel, and according to the occurrence of the crossflow, a fluid production profile test is performed on the target well. After the corresponding dominant seepage channel is obtained, the method further includes:

[0096] The dominant seepage channel is blocked to ensure normal production of the target well.

[0097] It can be understood that in some embodiments, after the dominant seepage channel is identified, it needs to be blocked to prevent it from interfering with the normal production of the target well while ensuring production safety. Furthermore, in some embodiments, other dominant seepage channel identification methods can be used to re-evaluate the identified dominant seepage channel before blocking to ensure the accuracy of the identified dominant seepage channel and the effectiveness of the blocking operation.

[0098] Refer to the attached Figure 4 , in some embodiments, may further include:

[0099] S401: Obtain the historical salinity of the injection water samples of the well to be predicted and the historical salinity of the produced water samples at different sampling times;

[0100] Wherein, the well to be predicted and the target well are produced under the drive of the same injection well;

[0101] S402: Calculating historical ratios corresponding to historical salinity of the injected water sample and historical salinity of the produced water sample at different sampling times;

[0102] S403: establishing a fitting model using the historical ratio, and obtaining a predicted time for the occurrence of a dominant seepage channel in the well to be predicted based on the fitting model;

[0103] S404: verifying the predicted time according to the historical ratio, the crossflow occurrence of the target well, and the production correlation between the target well and the well to be predicted;

[0104] S405: If the verification fails, the parameters of the fitting model are adjusted until the prediction time verification passes, thereby obtaining a prediction time that meets the verification conditions.

[0105] It can be understood that, in some embodiments, for a certain well, the historical mineralization of the injected water samples and the historical mineralization of the produced water samples at different sampling times can be used to predict whether the well will have a dominant seepage channel. Specifically, the well to be predicted and the target well are produced under the drive of the same injection well. Therefore, when making the prediction, the injected water sample obtained by sampling from the same injection well can be used.

[0106] Furthermore, in some embodiments, after obtaining the historical mineralization of the injected water samples and the historical mineralization of the produced water samples of the well to be predicted and at different sampling times, the historical ratios corresponding to the historical mineralization of the injected water samples and the historical mineralization of the produced water samples at different sampling times can be calculated to establish a fitting model based on the historical ratios, and the future ratios can be predicted based on the fitting model to determine whether the future ratios exceed a preset threshold. If the preset threshold is not exceeded, the injection medium does not flow along the dominant seepage channel. If the preset threshold is exceeded, it means that the injection medium flows along the dominant seepage channel. Based on the future time corresponding to the future ratio that exceeds the preset threshold, the predicted time of the appearance of the dominant seepage channel in the well to be predicted is obtained.

[0107] Furthermore, in some embodiments, after obtaining the predicted time when the dominant seepage channel appears in the predicted well, in order to ensure the validity of the predicted time, the predicted time can be verified based on the historical ratio, the occurrence of crossflow in the target well, and the production correlation between the target well and the well to be predicted. If the verification fails, the parameters of the fitting model are adjusted until the predicted time is verified and the predicted time that meets the verification conditions is obtained. This article does not limit the specific fitting algorithm of the fitting model.

[0108] Furthermore, in some embodiments, the occurrence of crossflow in the target well is obtained by monitoring the working conditions of the work area, and the production correlation between the target well and the well to be predicted is obtained by performing a correlation analysis on the target well and the well to be predicted. When verifying the prediction time, it is necessary to pre-establish a verification model, which performs a regression analysis on the historical ratios, the occurrence of crossflow in the target well, and the production correlation and prediction time between the target well and the well to be predicted, so as to determine the intrinsic correlation between the historical ratios, the occurrence of crossflow in the target well, and the production correlation and prediction time between the target well and the well to be predicted, so as to verify the prediction time and optimize the fitting model.

[0109] In order to facilitate the understanding of those skilled in the art, this specification gives a typical example. The permeability variation coefficient of the highly heterogeneous reservoir is 0.77. Figure 5 The well pattern distribution diagram corresponding to the highly heterogeneous reservoir shown is shown, where the letter P represents the well, and the number after P represents the well number. P3 is the injection well, P7 is the production well for which crossflow is to be predicted, and P12 is the production well for which crossflow has already occurred.

[0110] First, the corresponding injection water samples were obtained according to P3, and the corresponding produced water samples were obtained according to P7 and P12, respectively. The sampling period was 2006-2022. Then, the corresponding ion composition of the injection water samples and the produced water samples was determined. The mineralization of the injection water samples and the produced water samples were calculated based on the Sulin classification method. Specifically, there are many methods for classifying formation water types, such as the Sulin classification method, the Brodsky classification method, and the Shukarev classification method. Among them, the Brodsky classification method is relatively cumbersome, and it is not possible to understand the exact content of the chemical components in the water by naming. The Shukarev classification method does not consider the primary and secondary relationship when there are more than two cations (or anions) with a molar percentage greater than 25%. The Sulin classification method links the chemical composition of groundwater with the natural environmental conditions in which it is located, and uses different water types to represent different geological environments. It is suitable for the identification and prediction of dominant seepage channels in highly heterogeneous oil reservoirs. For the produced water sample of P12 in 2006, the cation Na required by the Sulin classification method + , K + Mg 2+ and Ca 2+ , anion Cl - 、SO4 2- 、HCO3 - and CO3 2- The corresponding mineralization is calculated to be 24362.90 mg / L. The specific produced water samples are shown in Table 1.

[0111] Table 1 Analysis results of produced water quality from well P12 in 2006

[0112]

[0113] After obtaining the mineralization of the injected water sample and the produced water sample, it is necessary to analyze the mineralization of the injected water sample and the produced water sample. For the convenience of intuitive analysis, the absolute sampling time (2006-2016) can be used as the horizontal axis, and the mineralization of the produced water of the production well P12 and the injected water of the injection well P3 can be used as the vertical axis to draw a bar graph of the mineralization of the produced water sample and the injected water sample and the absolute sampling time, as shown in the figure below. Figure 6 As shown, it can be seen that the salinity of the injected water from injection well P3 and the produced water from production well P12 in 2009 is similar, with a ratio of 0.88. 0.88>0.85, which preliminarily indicates that there is a dominant seepage channel between wells P3 and P12. A production profile test was conducted on well P12, and the test results are shown in the figure below. Figure 7 As shown in the results, the absolute liquid production of S2-Ⅰ layer is 81.9m 3 The relative liquid production was 77.19%, indicating that the S2-I layer in wells P3 and P12 is the dominant flow channel. This result is consistent with the results obtained by the method described in the present embodiment, demonstrating the reliability of this method. In some embodiments, to ensure normal production of the oil well, it is necessary to plug the S2-I layer.

[0114] Furthermore, in order to facilitate intuitive analysis and prediction of when crossflow may occur in P7, the relative sampling time corresponding to the absolute sampling time of 2006 is set as year 0, 2007 corresponds to year 1, and so on to 2016 as 10 years, which are used as the horizontal axis; the salinity ratio of the produced water of the production well P7 and the injected water of the injection well P3 is used as the vertical axis, and a scatter plot of the salinity ratio of the produced water sample and the injected water sample and the relative sampling time is drawn, as shown in the figure below: Figure 8 As shown in the figure, before P12 plugging, there are three independent scattered points. After P12 plugging, the fitted dashed curve corresponding to the scattered points can be expressed as y = 0.801ln(x) + 3.11. Let y = 1, and the solution is x = 13.93, indicating that if the construction system is not changed, the well will have a dominant seepage channel within 4 years (i.e., 2020). At the same time, the prediction results are verified by combining numerical simulation technology, as shown in the figure. Figure 9 As shown, the oil saturation of the S3-Ⅱ layer between the injection well P3 and the production well P7 in 2020 is 0.08, that is, the water saturation is 0.92, indicating that the injected water in 2020 flows from the injection well P3 to the production well P7 along the dominant seepage channel (S3-Ⅱ).

[0115] It should be noted that although the operations of the method of the present invention are described in a specific order in the above embodiments and drawings, this does not require or imply that these operations must be performed in this specific order, or that all illustrated operations must be performed to achieve the desired results. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0116] Corresponding to the above-mentioned method for identifying and predicting the dominant channel of flooding flow in a strongly heterogeneous reservoir, some embodiments of this specification further provide a device for identifying and predicting the dominant channel of flooding flow in a strongly heterogeneous reservoir, referring to Figure 10 As shown, in some embodiments, the apparatus may include:

[0117] Receiving module 1001, used to obtain injected water samples and produced water samples corresponding to the target well;

[0118] Determination module 1002, for determining the ion composition corresponding to the injected water sample and the produced water sample;

[0119] A calculation module 1003 is used to calculate the salinity of the injected water sample and the salinity of the produced water sample according to the ion composition using a preset classification standard;

[0120] The analysis module 1004 is used to analyze the correlation between the salinity of the injected water sample and the salinity of the produced water sample at different sampling times, so as to obtain the corresponding dominant seepage channel according to the correlation.

[0121] For the convenience of description, the above devices are described as being divided into various units according to their functions. Of course, when implementing this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0122] It should be noted that in the embodiments of this specification, the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved are all information and data authorized by the user and fully authorized by all parties.

[0123] It should be noted that the computer program product described in this specification is a software product that mainly implements the method described in this specification through a computer program.

[0124] The embodiment of this specification also provides a computer device. Figure 11As shown, in some embodiments of the present specification, the computer device 1102 may include one or more processors 1104, such as one or more central processing units (CPUs) or graphics processing units (GPUs), and each processing unit may implement one or more hardware threads. The computer device 1102 may also include any memory 1106, which is used to store any kind of information such as code, settings, data, etc. In a specific embodiment, the computer program on the memory 1106 and executable on the processor 1104, when the computer program is executed by the processor 1104, can execute the instructions of the method described in any of the above embodiments. For example, without limitation, the memory 1106 may include any one or more combinations of the following: any type of RAM, any type of ROM, a flash memory device, a hard disk, an optical disk, etc. More generally, any memory may use any technology to store information.

[0125] Furthermore, any memory may provide volatile or non-volatile retention of information. Further, any memory may represent a fixed or removable component of the computer device 1102. In one embodiment, when the processor 1104 executes the associated instructions stored in any memory or combination of memories, the computer device 1102 may perform any operation of the associated instructions. The computer device 1102 also includes one or more drive mechanisms 1108 for interacting with any memory, such as a hard disk drive mechanism, an optical disk drive mechanism, etc.

[0126] The computer device 1102 may also include an input / output interface 1110 (I / O) for receiving various inputs (via input devices 1112) and for providing various outputs (via output devices 1114). A specific output mechanism may include a presentation device 1116 and an associated graphical user interface 1118 (GUI). In other embodiments, the input / output interface 1110 (I / O), input devices 1112, and output devices 1114 may not be included, and the computer device 1102 may simply be a computer device in a network. The computer device 1102 may also include one or more network interfaces 1120 for exchanging data with other devices via one or more communication links 1122. One or more communication buses 1124 couple the components described above together.

[0127] The communication link 1122 may be implemented in any manner, for example, via a local area network, a wide area network (e.g., the Internet), a point-to-point connection, etc., or any combination thereof. The communication link 1122 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc., governed by any protocol or combination of protocols.

[0128] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), computer-readable storage media, and computer program products of some embodiments of the present specification. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processor to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processor generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0129] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processor to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, the instruction device being implemented in the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0130] These computer program instructions can also be loaded onto a computer or other programmable data processor so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0131] In a typical configuration, a computer device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0132] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0133] Computer-readable media include permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computer device. As defined in this specification, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0134] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems, or computer program products. Therefore, the embodiments of this specification may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the embodiments of this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0135] Embodiments of this specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, and the like that perform specific tasks or implement specific abstract data types. Embodiments of this specification may also be practiced in distributed computing environments where tasks are performed by remote processors connected via a communications network. In distributed computing environments, program modules may be located in local and remote computer storage media, including storage devices.

[0136] It should also be understood that in the embodiments of this specification, the term "and / or" is merely a description of the association relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. Furthermore, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.

[0137] The various embodiments in this specification are described in a progressive manner. Similar parts between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the system embodiments are generally similar to the method embodiments, so the description is relatively simple. For relevant parts, refer to the description of the method embodiments.

[0138] In the description of this specification, the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the embodiments of this specification. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0139] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A method for identifying and predicting dominant flow channels in highly heterogeneous reservoirs, characterized by: The method comprises: Obtain injection water samples and produced water samples corresponding to the target well; Determining the ion composition of the injected water sample and the produced water sample; Calculating the salinity of the injected water sample and the salinity of the produced water sample using a preset classification standard based on the ion composition; Analyze the correlation between the salinity of the injected water sample and the salinity of the produced water sample at different sampling times, so as to obtain the corresponding dominant seepage channel according to the correlation; Analyze the correlation between the salinity of the injected water sample and the salinity of the produced water sample at different sampling times to obtain the corresponding dominant seepage channel based on the correlation, including: Calculate the ratio between the salinity of the injected water sample and the salinity of the produced water sample at different sampling times; Determine whether the ratios at different sampling times exceed a preset threshold; If the preset threshold is not exceeded, the injection medium does not flow along the dominant seepage channel; If the preset threshold is exceeded, the injection medium will flow along the dominant seepage channel. Based on the occurrence of crossflow, the target well will be tested for the production profile to obtain the corresponding dominant seepage channel.

2. The method according to claim 1, characterized in that The preset classification standard is the Sulin classification standard.

3. The method according to claim 2, characterized in that Based on the ion composition, the salinity of the injected water sample and the salinity of the produced water sample are calculated using a preset classification standard, including: Cations and anions corresponding to the Sulin classification standard are selected from the ion composition, and the mineralization of the injected water sample and the mineralization of the produced water sample are calculated based on the selection results.

4. The method according to claim 1, wherein If the preset threshold is exceeded, the injection medium will flow along the dominant seepage channel. The target well will be tested for the production profile according to the occurrence of crossflow. After the corresponding dominant seepage channel is obtained, the following steps will be further performed: The dominant seepage channel is blocked to ensure normal production of the target well.

5. The method according to claim 1, wherein Further including: Obtaining historical salinity of injection water samples and produced water samples of the predicted well and the target well at different sampling times; wherein the predicted well and the target well are produced under the drive of the same injection well; Calculate the historical ratios of the historical salinity of the injected water samples and the historical salinity of the produced water samples at different sampling times; Establishing a fitting model using the historical ratio, and obtaining a predicted time for the appearance of a dominant seepage channel in the well to be predicted based on the fitting model; Verifying the predicted time based on the historical ratio, crossflow occurrence of the target well, and production correlation between the target well and the well to be predicted; If the verification fails, the parameters of the fitting model are adjusted until the predicted time verification passes, thereby obtaining a predicted time that meets the verification conditions.

6. The device for identifying and predicting the dominant flow channel of injection and flooding in highly heterogeneous reservoirs is characterized by: A method for identifying and predicting dominant flow channels in highly heterogeneous reservoirs according to any one of claims 1 to 5 is implemented, wherein the device comprises: A receiving module is used to obtain injected water samples and produced water samples corresponding to the target well; A determination module, configured to determine the ion composition corresponding to the injected water sample and the produced water sample; a calculation module, configured to calculate the mineralization of the injected water sample and the mineralization of the produced water sample according to the ion composition and using a preset classification standard; The analysis module is used to analyze the correlation between the salinity of the injected water sample and the salinity of the produced water sample at different sampling times, so as to obtain the corresponding dominant seepage channel according to the correlation.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory, characterized in that: When the computer program is executed by the processor, the computer program executes the instructions of the method according to any one of claims 1 to 5.

8. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor of a computer device, the computer program executes the instructions of the method according to any one of claims 1 to 5.

9. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the computer program executes instructions of the method according to any one of claims 1 to 5.

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