Oil reservoir water flooded layer identification method, device, equipment and medium

Abstract

The invention relates to the technical field of combination flooding water flooded layer recognition, and discloses an oil reservoir water flooded layer recognition method, device, equipment and medium, and the method comprises the steps: carrying out combination flooding experiments on different lithology, mineralization degrees and pore structures under stratum conditions, and obtaining a reservoir four-relation change rule of a combination flooding water flooded layer; a reservoir four-relation change rule is analyzed, and a water logging degree qualitative identification model is established; according to the model, performing interpretation model analysis of layering and lithological combination flooding pore saturation, shale content and water production rate, establishing a combination flooding water flooded layer subdivision evaluation scheme and standard, and performing combination flooding water flooded layer monitoring evaluation by utilizing a static well logging method in combination with casing well logging dynamic parameters to obtain combination flooding water flooded layer monitoring evaluation data; and constructing a discrimination chart in combination with a water flooding experiment of the water-flooded reservoir to determine a plane distribution rule of the water-flooded reservoir of the combination flooding reservoir. Therefore, the oil reservoir water flooded layer can be accurately identified, the plane distribution rule is determined, the measurement precision is high, the working efficiency is high, and the cost is low.

Description

Technical Field

[0001] This invention relates to the field of composite water-flooded layer identification technology, and in particular to a method, apparatus, equipment and medium for identifying water-flooded layers in oil reservoirs. Background Technology

[0002] The oilfield's composite flooding zones exhibit severe intra-layer heterogeneity, employing various displacement methods such as freshwater flooding, wastewater flooding, polymer flooding, and composite flooding. The complex reservoir properties, oil content, formation pressure, and water characteristics result in a complicated distribution of water-flooded layers. To clarify the distribution of water-flooded layers and improve oil recovery, it is necessary to conduct key technical analyses for a detailed description of water-flooded layers in sandstone and conglomerate composite flooding.

[0003] In the later stages of oilfield development, most oilfields require water injection to replenish reservoir energy, which easily leads to water flooding. Because currently developed reservoirs often exhibit strong heterogeneity, the water flooding patterns are extremely complex. Current technical solutions for identifying water-flooded layers largely require comprehensive analysis of geological, logging, development history, and well logging data. This process is complex, time-consuming, and lacks sufficient accuracy, failing to meet the timeliness requirements for on-site evaluation. Existing technologies for analyzing the influencing factors and variation patterns of composite flooding water-flooded layers are ineffective, and the qualitative identification accuracy of water flooding severity is low.

[0004] Therefore, how to provide an effective method for rapid identification of water-flooded layers in highly heterogeneous oil reservoirs is a technical problem that urgently needs to be solved by those in the field. Summary of the Invention

[0005] The purpose of this invention is to provide a method, apparatus, equipment, and medium for identifying water-flooded layers in oil reservoirs, which can accurately identify water-flooded layers in oil reservoirs and determine their planar distribution patterns, with high measurement accuracy, high working efficiency, and low cost.

[0006] To address the aforementioned technical problems, this invention provides a method for identifying water-flooded layers in oil reservoirs, the method comprising:

[0007] Composite flooding experiments were conducted on different lithologies, mineralization, and pore structures under different formation conditions to obtain the variation law of the four reservoir properties in composite flooding water-flooded layers.

[0008] Analyze the changing patterns of the four reservoir properties in a composite flooded reservoir and establish a qualitative identification model for the degree of flooding.

[0009] Based on the qualitative identification model of the degree of flooding, the composite flooding pore saturation, clay content, and water production rate of the lithology are analyzed to establish a detailed evaluation scheme and standard for composite flooding layers.

[0010] Based on the aforementioned composite water flooding layer subdivision evaluation scheme and standard, the composite water flooding layer monitoring and evaluation is carried out by using static logging methods combined with casing logging dynamic parameters, and the composite water flooding layer monitoring and evaluation data is obtained.

[0011] Based on the monitoring and evaluation data of the composite flooding reservoir and the water-flooding experiment, a discrimination chart was constructed using data from open-hole and cased wells as well as regional geological data. The planar distribution pattern of the composite flooding reservoir water-flooded layer was then determined based on the discrimination chart.

[0012] In a first aspect, the reservoir water-flooded layer identification method provided by the present invention establishes a qualitative identification model for the degree of water flooding, including:

[0013] Images of the water-flooded reservoir were acquired and corrected. Image recognition methods were used to identify the four properties of the water-flooded reservoir and extract relevant information on the four properties of the water-flooded reservoir.

[0014] The identified water-flooded reservoirs are matched with dynamic casing logging to determine the dynamic casing logging to which each water-flooded reservoir belongs.

[0015] Based on the dynamic casing logging of each water-flooded reservoir and the four properties related to the water-flooded reservoir, the lithology, physical properties, electrical properties, and oil content of the water-flooded reservoir are calculated.

[0016] Store the electrical and oil-bearing properties of each water-flooded reservoir from each well log and output them in a format compatible with bar charts.

[0017] On the other hand, in the above-mentioned method for identifying water-flooded reservoirs provided by the present invention, the acquisition and correction of water-flooded reservoir images includes:

[0018] The water-flooded reservoir is placed into the standard water-flooded reservoir four properties in the set order, and the water-flooded reservoir identification device is inserted at the corresponding well logging depth.

[0019] Using the water-flooded reservoir identification device and the vertical orthophoto method, images of the water-flooded reservoir are obtained, resulting in a set of images of the whole-type water-flooded reservoir.

[0020] The images in the image set of the whole-type water-flooded reservoir are corrected to obtain the orthophoto of the whole-type water-flooded reservoir.

[0021] On the other hand, in the above-mentioned reservoir water-flooded layer identification method provided by the present invention, the images in the image set of the whole-four water-flooded layer reservoir are corrected to obtain an orthophoto of the whole-four water-flooded layer reservoir, including:

[0022] Align the four corner points of the image in the image set of the whole-type water-flooded reservoir with the four corner points of the rectangular frame of the image processing interface to obtain the orthophoto image of the whole-type water-flooded reservoir.

[0023] On the other hand, in the above-mentioned method for identifying water-flooded reservoirs provided by the present invention, image recognition methods are used to perform morphological identification of the four properties of the water-flooded reservoir and extract relevant information on the four properties of the water-flooded reservoir, including:

[0024] The image recognition method is used to perform morphological recognition of the four properties of water-flooded reservoirs, extract the four property information of water-flooded reservoirs, and obtain the ratio of image pixels to actual four property thresholds by inputting the four property thresholds of water-flooded reservoirs.

[0025] A high-precision water-flooded reservoir feature segmentation algorithm based on deep learning identifies the morphological features of the water-flooded reservoir, classifies the morphology of the water-flooded reservoir, and distinguishes them using different colors.

[0026] Extract the four property thresholds, width, and geometric features of the corresponding water-flooded reservoir, and calculate the actual geometric parameters of each water-flooded reservoir by combining the ratio of the image pixels to the actual four property thresholds, and extract the column length information of the water-flooded reservoir.

[0027] The water-flooded reservoir identification device is identified and marked with corresponding colors to determine the specific location of each dynamic casing logging operation. The corresponding information is obtained by matching it with the input logging information data.

[0028] On the other hand, in the above-mentioned method for identifying water-flooded reservoirs provided by the present invention, a detailed evaluation scheme and standard for composite water-flooded reservoirs are established, including:

[0029] By using data from open-hole and cased wells, as well as regional geological data, we can track and interpret the composite water-flooded layers to identify their distribution characteristics.

[0030] The study area was identified in terms of stratification, excluding the composite flooding layer, and the interpretation models for the variation of pore saturation, clay content, and water production rate of the composite flooding strata, lithology, and water production rate, as well as the channel types and distribution characteristics.

[0031] Analyze the distribution and amplitude characteristics of oil and gas reservoirs or natural gas hydrate reservoirs in the upper strata of the composite water-flooded layer to determine whether they contain oil and gas reservoirs.

[0032] Based on the established distribution characteristics, we analyze the variation channels of the composite flooding layer, other layers, and lithological composite flooding pore saturation, clay content, and water production rate interpretation models, as well as the distribution and spatial matching relationship of oil and gas reservoirs or natural gas hydrate reservoirs in shallow strata.

[0033] To evaluate the role of composite water-flooded layers in the formation of shallow oil reservoirs, including the interpretation of variations in stratification, lithology, composite pore-permeability saturation, clay content, water production rate, and the function of composite water-flooded layers in the formation of oil reservoirs.

[0034] On the other hand, in the above-mentioned reservoir water-flooded layer identification method provided by the present invention, determining the distribution characteristics of the composite water-flooded layer includes:

[0035] By interpreting faults in vertical open-hole and cased-hole data and regional geological profiles, we can analyze the stratigraphic interpretation of the composite water-flooded layer and extract the properties of planar coherent bodies to determine its morphological characteristics.

[0036] The planar geometry of the composite water-flooding layer is identified by time coherence attribute maps. Combined with data from open-hole and cased wells and the interpretation results of regional geological profiles, it is determined whether the composite water-flooding layer has strata control, its extension length, and its burial depth and thickness.

[0037] The lithological characteristics of the composite water-flooded layer are determined by using well logging or core data, so as to determine the genetic type of the composite water-flooded layer.

[0038] To address the aforementioned technical problems, the present invention also provides a reservoir water-flooded layer identification device, the device comprising:

[0039] The composite flooding experimental module is used to conduct composite flooding experiments on different lithologies, mineralization, and pore structures under formation conditions to obtain the variation law of the four reservoir properties in composite flooding water-flooded layers.

[0040] The identification model building module is used to analyze the changing patterns of the four properties of reservoirs in composite flooded reservoirs and to establish a qualitative identification model for the degree of flooding.

[0041] The variation law analysis module is used to perform stratification based on the qualitative identification model of the flooding degree, analyze the interpretation model of composite flooding pore saturation, clay content, and water production rate according to lithology, and establish a subdivision evaluation scheme and standard for composite flooding layer.

[0042] The monitoring and evaluation module is used to monitor and evaluate the composite water flooding layer according to the subdivided evaluation scheme and standards of the composite water flooding layer, using static logging methods combined with dynamic parameters of casing logging, and to obtain composite water flooding layer monitoring and evaluation data.

[0043] The distribution pattern determination module is used to construct a discrimination chart based on the monitoring and evaluation data of the composite flooding reservoir and the water flooding experiment, using data from open hole wells and casing wells as well as regional geological data, and to determine the planar distribution pattern of the water flooding layer in the composite flooding reservoir based on the discrimination chart.

[0044] To address the aforementioned technical problems, the present invention also provides a reservoir water-flooded layer identification device, the device comprising:

[0045] Memory, used to store computer programs;

[0046] A processor is used to implement the steps of the above-described method for identifying water-flooded reservoirs when executing the computer program.

[0047] To address the aforementioned technical problems, the present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described method for identifying water-flooded reservoir layers.

[0048] As can be seen from the above technical solution, the present invention provides a method for identifying water-flooded reservoirs. This method includes: conducting composite flooding experiments on different lithologies, mineralization, and pore structures under formation conditions to obtain the changing patterns of the four reservoir properties (water-flooded reservoir, pore saturation, clay content, and water production rate) in composite flooding reservoirs; analyzing the changing patterns of the four reservoir properties in composite flooding reservoirs and establishing a qualitative identification model for the degree of water flooding; performing stratification based on the qualitative identification model for the degree of water flooding, analyzing interpretation models for lithology-specific composite flooding pore saturation, clay content, and water production rate, and establishing a detailed evaluation scheme and standard for composite flooding reservoirs; monitoring and evaluating composite flooding reservoirs using static logging methods combined with dynamic parameters from casing logging, based on the detailed evaluation scheme and standard, to obtain monitoring and evaluation data for composite flooding reservoirs; constructing a discrimination chart using data from open-hole wells, casing wells, and regional geological data, based on the monitoring and evaluation data of composite flooding reservoirs and water-flooding experiments, and determining the planar distribution pattern of water-flooded reservoirs in composite flooding reservoirs based on the discrimination chart.

[0049] The beneficial effects of this invention are as follows: the above-mentioned method for identifying water-flooded reservoirs provided by this invention eliminates the need for manual on-site measurement of the four threshold values ​​of electrical properties, oil content, and other properties of water-flooded reservoirs, resulting in high measurement accuracy and reduced labor costs. Furthermore, the method enables identification and interpretation of water-flooded reservoirs, providing image reproduction and result verification functions. Based on the qualitative identification model of water-flooding degree, the method analyzes the interpretation models of composite flooding permeability saturation, clay content, and water production rate of surrounding strata and lithologies, establishing a detailed evaluation scheme and standard for composite flooding water-flooded layers to obtain monitoring and evaluation data of composite flooding water-flooded layers. This helps to objectively evaluate its impact on shallow oil and gas or hydrate accumulation and enables researchers to correctly understand the accumulation mode of water-flooded reservoirs.

[0050] In addition, the present invention also provides a corresponding reservoir water-flooded layer identification device, reservoir water-flooded layer identification equipment, and computer-readable storage medium for the reservoir water-flooded layer identification method, which have the same or corresponding technical features as the reservoir water-flooded layer identification method mentioned above, and have the same effect. Attached Figure Description

[0051] To more clearly illustrate the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 A flowchart of the reservoir water-flooded layer identification method provided in the embodiments of the present invention;

[0053] Figure 2 This is a schematic diagram of the main reservoir parameter curve analysis provided in the embodiments of the present invention;

[0054] Figure 3 This is a schematic diagram of the structure of the reservoir water-flooded layer identification device provided in an embodiment of the present invention;

[0055] Figure 4 This is a schematic diagram of the structure of the reservoir water-flooded layer identification device provided in an embodiment of the present invention. Detailed Implementation

[0056] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the protection scope of the present invention.

[0057] To enable those skilled in the art to better understand the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Figure 1 The flowchart of the reservoir water-flooded layer identification method provided in the embodiments of the present invention is as follows: Figure 1 As shown, the method includes:

[0058] S101. Conduct composite flooding experiments on different lithologies, mineralization, and pore structures under formation conditions to obtain the variation law of the four reservoir properties in composite flooding water-flooded layers.

[0059] The composite flooding experiment in the above steps can be selected from the composite flooding water flooding mechanism experiment; the composite flooding water flooding mechanism experiment can be used to conduct composite flooding experiments with different lithologies, mineralization and pore structures under formation conditions, and to obtain the influencing factors and variation laws of the composite flooding water flooding layer.

[0060] S102. Analyze the changing patterns of the four properties of the reservoir in the composite flooding layer and establish a qualitative identification model for the degree of flooding.

[0061] The above steps can be understood as the analysis of the four properties of a water-flooded reservoir and the characteristics of its logging response. The changes in the four properties of the reservoir after the composite flooding mechanism experiment are analyzed, and a qualitative identification model for the degree of water flooding is established. The four properties of a water-flooded reservoir include: lithology, physical properties, electrical properties, and oil content; among which, physical properties include porosity and permeability.

[0062] S103. Based on the qualitative identification model of the degree of flooding, the composite flooding pore saturation, clay content, and water production rate of the lithology are analyzed to establish a detailed evaluation scheme and standard for composite flooding layers.

[0063] The above steps can be understood as the analysis of parameter models and variation patterns of high water-cut reservoirs. This invention can perform interpretive model analysis of composite flooding permeability saturation, clay content, and water production rate based on a qualitative identification model of water flooding degree, and establish a detailed evaluation method and standard for composite flooding water-flooded layers based on the analysis results.

[0064] S104. Based on the evaluation scheme and standards for the subdivision of the composite water-flooded layer, the composite water-flooded layer is monitored and evaluated using static logging methods combined with dynamic parameters from casing logging, and the monitoring and evaluation data of the composite water-flooded layer are obtained.

[0065] The above steps can be understood as technical analysis of water-flooded formation monitoring and evaluation. This invention, based on the established methods and standards for detailed evaluation of composite water-flooded formations, utilizes static logging technology combined with dynamic parameters from casing logging to monitor and evaluate composite water-flooded formations. Casing logging here can include Reservoir Monitoring Tool (RMT), C / O energy spectrum logging, oxygen activation, and Pulse Neutron Neutron (PNN) logging, etc.

[0066] S105. Based on the monitoring and evaluation data of the composite flooding reservoir and the water-flooding experiment, a discrimination chart is constructed using data from open-hole wells, casing wells, and regional geological data. The planar distribution pattern of the composite flooding reservoir water-flooded layer is then determined based on the discrimination chart.

[0067] The above steps can be understood as the analysis of the distribution of water-flooded layers in the analysis area. This invention can construct a discrimination chart based on the acquired monitoring and evaluation data of the composite flooding water-flooded layer, and on water-flooding experiments in the water-flooded reservoir, using data from open-hole and cased-hole wells, combined with regional geological data. The planar distribution pattern of the water-flooded layer in the composite flooding reservoir can then be determined based on this discrimination chart.

[0068] The oil reservoir water-flooded layer identification method provided in this invention can be automatically identified and processed by a computer, eliminating the need for manual on-site measurement of the four property thresholds of electrical properties and oil-bearing properties of the water-flooded reservoir. This method offers high measurement accuracy, reduces labor costs, and improves work efficiency. Furthermore, it enables identification and interpretation of water-flooded reservoirs, providing image reproduction and result verification functions. Based on a qualitative identification model of water-flooding degree, it analyzes interpretation models of surrounding strata, lithologies, composite flooding permeability saturation, clay content, and water production rate, establishing a detailed evaluation scheme and standards for composite flooding water-flooded layers. This yields monitoring and evaluation data for composite flooding water-flooded layers, which helps to objectively evaluate their impact on shallow oil and gas or hydrate accumulation, and assists researchers in correctly understanding the oil reservoir water-flooded layer accumulation model.

[0069] Furthermore, in specific implementation, in the above-mentioned reservoir water-flooded layer identification method provided in the embodiments of the present invention, step S102, establishing a qualitative identification model for the degree of water flooding, may specifically include:

[0070] Step 1: Acquire and correct images of the water-flooded reservoir, use image recognition methods to perform morphological identification of the four properties of the water-flooded reservoir, and extract relevant information on the four properties of the water-flooded reservoir.

[0071] Step 2: Match the identified water-flooded reservoirs with dynamic casing logging to determine the dynamic casing logging associated with each water-flooded reservoir.

[0072] Step 3: Based on the dynamic casing logging and the four properties of the water-flooded reservoir, calculate the lithology, physical properties, electrical properties, and oil content of the water-flooded reservoir.

[0073] Step 4: Store the electrical and oil-bearing properties of each water-flooded reservoir from each well log and output them in a format compatible with the bar chart.

[0074] In specific implementation, step one above, which involves acquiring and correcting images of the water-flooded reservoir, may include: first, placing the water-flooded reservoir into the standard four properties of the water-flooded reservoir in a predetermined order, and inserting a water-flooded reservoir identification device at the corresponding well depth; then, using the water-flooded reservoir identification device and a vertical orthophoto method, acquiring images of the water-flooded reservoir to obtain a set of images of the water-flooded reservoir with the four properties; finally, correcting the images in the set of images of the water-flooded reservoir with the four properties to obtain an orthophoto image of the water-flooded reservoir with the four properties.

[0075] In practice, the above steps involve correcting the images in the image set of the four-type water-flooded reservoir to obtain an orthophoto of the four-type water-flooded reservoir. Specifically, this may include aligning the four corner points of the image in the image set of the four-type water-flooded reservoir with the four corners of the rectangular frame of the image processing interface to obtain an orthophoto of the four-type water-flooded reservoir.

[0076] Furthermore, in specific implementation, step one above involves using image recognition methods to perform morphological identification of the four properties of the water-flooded reservoir and extracting relevant information on these properties. Specifically, this may include:

[0077] The first step is to use image recognition methods to perform morphological recognition of the four properties of the water-flooded reservoir, extract the four property information of the water-flooded reservoir, and obtain the ratio of image pixels to actual four property thresholds by inputting the four property thresholds of the water-flooded reservoir.

[0078] The second step is to use a high-precision water-flooded reservoir feature segmentation algorithm based on deep learning to identify the morphological features of the water-flooded reservoir, classify the morphology of the water-flooded reservoir, and distinguish them using different colors.

[0079] The third step is to extract the four property thresholds, width, and geometric features of the corresponding water-flooded reservoir, and to convert the actual geometric parameters of each water-flooded reservoir by combining the ratio of image pixels to the actual four property thresholds, and to extract the column length information of the water-flooded reservoir. Figure 2 This is a schematic diagram of the main reservoir parameter curve analysis provided in the embodiments of the present invention;

[0080] The fourth step is to identify the water-flooded reservoir identification equipment and mark it with the corresponding color to determine the specific location of each dynamic casing logging. The corresponding information is obtained by matching it with the input logging information data.

[0081] In implementation, the image recognition method in the first step can employ a neural network-based image recognition approach. The high-precision water-flooded reservoir feature segmentation algorithm based on deep learning in the second step can utilize a target segmentation algorithm based on multi-window local fractal features. According to this algorithm, the water-flooded reservoir morphology can be classified into clastic, blocky, semi-columnar, disc-shaped, short columnar, columnar, and long columnar types. This invention adopts a unified four-property threshold measurement standard, further improving measurement accuracy.

[0082] Furthermore, in specific implementation, in step three above, based on the dynamic casing logging and the four properties of the water-flooded reservoir to which each water-flooded reservoir belongs, the lithology, physical properties, electrical properties, and oil-bearing properties of the water-flooded reservoir are calculated. Specifically, this may include: calculating the number of water-flooded reservoir blocks in each logging session. Statistical analysis was performed on the four threshold values, and the first value was calculated. The cumulative threshold values ​​of the four properties of well logging: lithology, physical properties, electrical properties, and oil-bearing properties of the water-flooded reservoir. The expression is:

[0083] ;

[0084] in, Indicates the well logging number. This represents the threshold values ​​for the four properties.

[0085] In practical implementation, step three above involves establishing a detailed evaluation scheme and standards for the composite flooding layer, which may specifically include:

[0086] First, by using data from open-hole and cased-hole wells, as well as regional geological data, we tracked and interpreted the composite water-flooding layer to identify its distribution characteristics.

[0087] Then, the strata in the study area, excluding the composite flooding layer, were determined, and the interpretation models for the composite flooding pore saturation, clay content, and water production rate, as well as the channel types and distribution characteristics, were analyzed.

[0088] Next, the distribution and amplitude characteristics of oil and gas reservoirs or natural gas hydrate reservoirs in the upper strata of the composite water-flooded layer are analyzed to determine whether oil and gas reservoirs are present. Specifically, oil and gas reservoirs can be determined based on open-hole well, cased well, and regional geological data. Reflection layers in the upper strata can be identified using open-hole well, cased well, and regional geological data to determine whether oil and gas reservoirs are present.

[0089] Subsequently, based on the determined distribution characteristics, the interpretation models of the composite flooding layer, other layers, lithological composite flooding pore saturation, clay content, and water production rate were analyzed, as well as the distribution and spatial matching relationship of oil and gas reservoirs or natural gas hydrate reservoirs in shallow strata.

[0090] Finally, the study evaluates the role of composite flooding in the formation of shallow oil reservoirs, including the interpretation of variations in the composite flooding pore saturation, clay content, and water production rate by stratification and lithology.

[0091] In practice, this invention can track and finely interpret data from open-hole wells, casing wells, and regional geological data to identify and determine the distribution characteristics of composite water-flooded layers. These distribution characteristics include: the development depth and morphological characteristics of the composite water-flooded layers, as well as the lithological characteristics of the strata within the composite water-flooded layers. The development depth and morphological characteristics of the composite water-flooded layers include thickness, burial depth, and geometric features. The lithological characteristics of the strata within the composite water-flooded layers include the lithological characteristics of the layers where the composite water-flooded layers develop.

[0092] Determining the distribution characteristics of composite water-flooded layers can specifically include: interpreting faults in vertical open-hole and cased-hole well data and regional geological profiles; analyzing the morphological characteristics of composite water-flooded layers through stratigraphic interpretation and planar coherence body attribute extraction; identifying the planar geometry of composite water-flooded layers through time coherence attribute maps; and determining whether the composite water-flooded layers have strata control, their extension length, burial depth, and thickness by combining open-hole and cased-hole well data and the interpretation results of regional geological profiles; and using well logging or core data to determine the lithological characteristics of the layers developing from the composite water-flooded layers to determine the genetic type of the composite water-flooded layers.

[0093] Furthermore, in practice, this invention can determine the interpretation model variation channel types and distribution characteristics of composite flooding pore saturation, clay content, and water production rate in the study area, excluding composite flooding layers, based on stratification and lithology. Specifically, it can include: identifying gas chimneys based on open-hole and cased-hole data and regional geological profiles showing poor continuity, weak coherence, and weak energy characteristics; identifying diapiric structures based on obvious wave velocity anomalies; and identifying unconformities and permeable inclined sandstone formations based on open-hole and cased-hole data from interconnected wells in the study area, data from open-hole and cased-hole data from regional geological profiles, and regional geological reflection termination types, combined with drilling geological data analysis.

[0094] Furthermore, the determination of whether an oil and gas reservoir exists in the above steps may specifically include:

[0095] Step 1: In composite water-flooded oil and gas reservoirs, based on the main controlling factors of reservoir trap formation, the oil and gas reservoirs can be divided into fault oil and gas reservoirs, fault-oil-bearing oil and gas reservoirs, and oil-bearing-fault oil and gas reservoirs.

[0096] Step 2: For fault-controlled oil and gas reservoirs, the reservoirs are first classified into single-fault controlled, double-fault controlled, and multi-fault controlled reservoirs based on the number of faults controlling them.

[0097] Step 3: Classify oil and gas reservoirs controlled by a single fault;

[0098] In practice, for oil and gas reservoirs controlled by a single fault, the specific classifications can include: first, based on the planar morphology of the fault, they can be divided into arc-shaped and linear; second, based on the attitude of the fault and the strata, they can be divided into forward and reverse faults; then, based on the cross-sectional morphology of the fault, they can be divided into shovel-shaped and slab-shaped faults; finally, they can be determined as either a fault-block oil and gas reservoir or a fault-nose oil and gas reservoir, and the classification and naming can be based on a combination of all the above factors.

[0099] Step 4: Classify oil and gas reservoirs controlled by two faults;

[0100] In practice, for oil and gas reservoirs controlled by two faults, the specific types can be: first, according to the planar combination of the faults, they can be divided into parallel, oblique, broom, ring, radial, and oblique types; then, according to the combination pattern of the two faults in the cross section, they can be divided into step type, graben type, horst type, "Y" type, same-direction "Y" type, reverse "Y" type, same-direction reverse "Y" type, "human" type, same-direction "human" type, "entry" type, and same-direction "entry" type; and finally, according to the cross section morphology of the main controlling fault, they can be divided into shovel type and plate type.

[0101] Step 5: Classify oil and gas reservoirs controlled by multiple faults;

[0102] In practice, oil and gas reservoirs controlled by multiple faults are classified to obtain the reservoir type. Specific methods include: first, analyzing the reservoir composition and the role of each fault; identifying a fault at the top that provides primary shielding, two or one fault on each side that provides sealing, and no fault at the bottom or one fault that serves as a boundary limit; reservoirs with more than four faults or faults of too low a fault level are not considered. The naming of oil and gas reservoirs controlled by multiple faults can be simplified to the classification rules for reservoirs controlled by two faults; after simplification, the classification method for reservoirs controlled by two faults can be followed, i.e., step 4; finally, the classification and naming are determined by comprehensively considering all the above factors.

[0103] Step 6: Classify the different types of oil reservoirs and summarize them to complete the classification of composite water-flooded oil and gas reservoirs.

[0104] Step 6 above is to finally summarize the different types of reservoirs after completing steps 1 to 5, and complete the classification of composite water-flooded oil and gas reservoirs.

[0105] This invention proposes qualitative and quantitative interpretation techniques and charts for heterogeneous composite flooding water-flooded layers. The relative errors of the main reservoir parameters are: porosity less than 8% and water saturation less than 10%; the interpretation accuracy of water-flooded layers is above 85%.

[0106] In the above embodiments, the method for identifying water-flooded layers in oil reservoirs has been described in detail. This invention also provides embodiments of a water-flooded layer identification device and a water-flooded layer identification equipment. It should be noted that this invention describes the embodiments of the device from two perspectives: one based on functional modules, and the other based on hardware.

[0107] Figure 3 This is a schematic diagram of the reservoir water-flooded layer identification device provided in an embodiment of the present invention. This embodiment is based on functional modules, such as… Figure 3 As shown, the device includes:

[0108] The composite flooding experiment module 10 is used to conduct composite flooding experiments on different lithologies, mineralization, and pore structures under formation conditions to obtain the variation law of the four reservoir properties of the composite flooding water-flooded layer.

[0109] The identification model establishment module 11 is used to analyze the changing law of the four properties of the reservoir in the composite flooding layer and to establish a qualitative identification model of the degree of flooding.

[0110] The variation law analysis module 12 is used to perform stratification based on the qualitative identification model of the degree of flooding, and to analyze the interpretation model of composite flooding pore saturation, clay content, and water production rate according to lithology, and to establish a detailed evaluation scheme and standard for composite flooding layer.

[0111] The monitoring and evaluation module 13 is used to monitor and evaluate the composite water flooding layer according to the subdivided evaluation scheme and standards of the composite water flooding layer, and to obtain the composite water flooding layer monitoring and evaluation data by using static logging methods combined with the dynamic parameters of casing logging.

[0112] The distribution pattern determination module 14 is used to construct a discrimination chart based on the monitoring and evaluation data of the composite flooding reservoir and the water flooding experiment of the water flooding reservoir, using data from open hole wells and casing wells as well as regional geological data, and to determine the planar distribution pattern of the water flooding layer of the composite flooding reservoir based on the discrimination chart.

[0113] In the reservoir water-flooded layer identification device provided in the embodiments of the present invention, the interaction of the above four modules can eliminate the need for manual on-site measurement of the electrical properties, oil content, and other four property thresholds of the water-flooded layer reservoir, thereby reducing labor costs and improving measurement accuracy. Furthermore, it can identify and interpret the water-flooded layer reservoir, and has the functions of image reproduction and result verification. Based on the qualitative identification model of water flooding degree, it analyzes the interpretation model of the surrounding stratification, lithology, composite flooding permeability saturation, clay content, and water production rate, and establishes a subdivided evaluation scheme and standard for composite flooding water-flooded layers to obtain monitoring and evaluation data of composite flooding water-flooded layers. This helps to objectively evaluate its impact on shallow oil and gas or hydrate accumulation and can help researchers correctly understand the reservoir water-flooded layer accumulation model.

[0114] Since the embodiments of the apparatus and the method correspond to each other, please refer to the description of the embodiments in the method section for the apparatus embodiments, which will not be repeated here. Furthermore, it has the same beneficial effects as the reservoir water-flooded layer identification method mentioned above.

[0115] Figure 4 This is a schematic diagram of the reservoir water-flooded layer identification device provided in an embodiment of the present invention. This embodiment is based on a hardware perspective, such as... Figure 4 As shown, the reservoir water-flooded layer identification device includes:

[0116] Memory 20 is used to store computer programs;

[0117] The processor 21 is used to execute a computer program to implement the steps of the reservoir water-flooded layer identification method mentioned in the above embodiments.

[0118] The processor 21 may include one or more processing cores, such as a quad-core processor or an octa-core processor. The processor 21 may be implemented using at least one of the following hardware forms: Digital Signal Processor (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 21 may also include a main processor and a coprocessor. The main processor, also known as the CPU, is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, the processor 21 may integrate a Graphics Processing Unit (GPU), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, the processor 21 may also include an Artificial Intelligence (AI) processor, which is used to handle computational operations related to machine learning.

[0119] The memory 20 may include one or more computer-readable storage media, which may be non-transitory. The memory 20 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In this embodiment, the memory 20 is used to store at least the following computer program 201, which, after being loaded and executed by the processor 21, is capable of implementing the relevant steps of the reservoir water-flooded layer identification method disclosed in any of the foregoing embodiments. In addition, the resources stored in the memory 20 may also include an operating system 202 and data 203, and the storage method may be temporary or permanent storage. The operating system 202 may include Windows, Unix, Linux, etc. The data 203 may include, but is not limited to, the data involved in the aforementioned reservoir water-flooded layer identification method.

[0120] In some embodiments, the reservoir water-flooded layer identification device may further include a display screen 22, an input / output interface 23, a communication interface 24, a power supply 25, and a communication bus 26. Those skilled in the art will understand that... Figure 4The structure shown does not constitute a limitation on the reservoir water-flooded layer identification device, and may include more or fewer components than shown. The reservoir water-flooded layer identification device provided in this embodiment includes a memory and a processor. When the processor executes the program stored in the memory, it can implement the aforementioned reservoir water-flooded layer identification method, achieving the same effect.

[0121] The present invention also provides an embodiment corresponding to a computer-readable storage medium. The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps described in the above-mentioned embodiment of the oil reservoir water-flooded layer identification method.

[0122] It is understood that if the methods in the above embodiments are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and executes all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks. The computer-readable storage medium provided by the present invention can implement the aforementioned method for identifying water-flooded reservoirs, with the same effect.

[0123] This invention also provides an information data processing terminal, which, when executed on an electronic device, provides a user input interface to implement the steps in the above-mentioned oil reservoir water-flooded layer identification method embodiment. The information data processing terminal is not limited to mobile phones, computers, or switches.

[0124] This invention also provides a server that, when executed on an electronic device, provides a user input interface to implement the steps in the above-mentioned oil reservoir water-flooded layer identification method embodiment.

[0125] This invention also provides an embodiment corresponding to a computer program product. The computer program product includes a computer program / instructions, which, when executed by a processor, implement the steps described in the above embodiment of the oil reservoir water-flooded layer identification method. The computer program product provided by this invention can implement the aforementioned oil reservoir water-flooded layer identification method, achieving the same results.

[0126] It should also be noted that, in this specification, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0127] The method, apparatus, equipment, and medium for identifying water-flooded layers in oil reservoirs provided by this invention have been described in detail above. The various embodiments in the specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section. It should be noted that those skilled in the art can make several improvements and modifications to this invention without departing from the principles of this invention, and these improvements and modifications also fall within the protection scope of this invention.

Claims

1. A method for identifying a watered-out layer of an oil reservoir, characterized by, The method includes: Composite flooding experiments were conducted on different lithologies, mineralization, and pore structures under different formation conditions to obtain the variation law of the four reservoir properties in composite flooding water-flooded layers. Analyze the changing patterns of the four reservoir properties in a composite flooded reservoir and establish a qualitative identification model for the degree of flooding. Based on the qualitative identification model of the degree of flooding, the composite flooding pore saturation, clay content, and water production rate of the lithology are analyzed to establish a detailed evaluation scheme and standard for composite flooding layers. Based on the aforementioned composite water flooding layer subdivision evaluation scheme and standard, the composite water flooding layer monitoring and evaluation is carried out by using static logging methods combined with casing logging dynamic parameters, and the composite water flooding layer monitoring and evaluation data is obtained. Based on the monitoring and evaluation data of the composite flooding reservoir and the water-flooding experiment, a discrimination chart was constructed using data from open-hole and cased wells as well as regional geological data. The planar distribution pattern of the composite flooding reservoir water-flooded layer was then determined based on the discrimination chart.

2. The method of identifying a watered-out reservoir according to claim 1, wherein, Establish a qualitative identification model for the degree of flooding, including: Images of the water-flooded reservoir were acquired and corrected. Image recognition methods were used to identify the four properties of the water-flooded reservoir and extract relevant information on the four properties of the water-flooded reservoir. The identified water-flooded reservoirs are matched with dynamic casing logging to determine the dynamic casing logging to which each water-flooded reservoir belongs. Based on the dynamic casing logging of each water-flooded reservoir and the four properties related to the water-flooded reservoir, the lithology, physical properties, electrical properties, and oil content of the water-flooded reservoir are calculated. Store the electrical and oil-bearing properties of each water-flooded reservoir from each well log and output them in a format compatible with bar charts.

3. The method of claim 2, wherein, Acquisition and correction of images of water-flooded reservoirs, including: The water-flooded reservoir is placed into the standard water-flooded reservoir four properties in the set order, and the water-flooded reservoir identification device is inserted at the corresponding well logging depth. Using the water-flooded reservoir identification device and the vertical orthophoto method, images of the water-flooded reservoir are obtained, resulting in a set of images of the whole-type water-flooded reservoir. The images in the image set of the whole-type water-flooded reservoir are corrected to obtain the orthophoto of the whole-type water-flooded reservoir.

4. The method for identifying water-flooded layers in an oil reservoir according to claim 3, characterized in that, The images in the image set of the whole-type water-flooded reservoir are corrected to obtain an orthophoto of the whole-type water-flooded reservoir, including: Align the four corner points of the image in the image set of the whole-type water-flooded reservoir with the four corner points of the rectangular frame of the image processing interface to obtain the orthophoto image of the whole-type water-flooded reservoir.

5. The method for identifying water-flooded layers in an oil reservoir according to claim 3, characterized in that, Image recognition methods were used to perform morphological identification of the four properties of water-flooded reservoirs and extract relevant information on these properties, including: The image recognition method is used to perform morphological recognition of the four properties of water-flooded reservoirs, extract the four property information of water-flooded reservoirs, and obtain the ratio of image pixels to actual four property thresholds by inputting the four property thresholds of water-flooded reservoirs. A high-precision water-flooded reservoir feature segmentation algorithm based on deep learning identifies the morphological features of the water-flooded reservoir, classifies the morphology of the water-flooded reservoir, and distinguishes them using different colors. Extract the four property thresholds, width, and geometric features of the corresponding water-flooded reservoir, and calculate the actual geometric parameters of each water-flooded reservoir by combining the ratio of the image pixels to the actual four property thresholds, and extract the column length information of the water-flooded reservoir. The water-flooded reservoir identification device is identified and marked with corresponding colors to determine the specific location of each dynamic casing logging operation. The corresponding information is obtained by matching it with the input logging information data.

6. The method for identifying water-flooded layers in an oil reservoir according to claim 1, characterized in that, Establish a detailed evaluation scheme and standards for composite flooding layers, including: By using data from open-hole and cased wells, as well as regional geological data, we can track and interpret the composite water-flooded layers to identify their distribution characteristics. The study area was identified in terms of stratification, excluding the composite flooding layer, and the interpretation models for the variation of pore saturation, clay content, and water production rate of the composite flooding strata, lithology, and water production rate, as well as the channel types and distribution characteristics. Analyze the distribution and amplitude characteristics of oil and gas reservoirs or natural gas hydrate reservoirs in the upper strata of the composite water-flooded layer to determine whether they contain oil and gas reservoirs. Based on the established distribution characteristics, we analyze the variation channels of the composite flooding layer, other layers, and lithological composite flooding pore saturation, clay content, and water production rate interpretation models, as well as the distribution and spatial matching relationship of oil and gas reservoirs or natural gas hydrate reservoirs in shallow strata. To evaluate the role of composite water-flooded layers in the formation of shallow oil reservoirs, including the interpretation of variations in stratification, lithology, composite pore-permeability saturation, clay content, water production rate, and the function of composite water-flooded layers in the formation of oil reservoirs.

7. The method for identifying water-flooded layers in an oil reservoir according to claim 6, characterized in that, Determine the distribution characteristics of the composite flooding layer, including: By interpreting faults in vertical open-hole and cased-hole data and regional geological profiles, we can analyze the stratigraphic interpretation of the composite water-flooded layer and extract the properties of planar coherent bodies to determine its morphological characteristics. The planar geometry of the composite water-flooding layer is identified by time coherence attribute maps. Combined with data from open-hole and cased wells and the interpretation results of regional geological profiles, it is determined whether the composite water-flooding layer has strata control, its extension length, and its burial depth and thickness. The lithological characteristics of the composite water-flooded layer are determined by using well logging or core data, so as to determine the genetic type of the composite water-flooded layer.

8. A device for identifying water-flooded layers in an oil reservoir, characterized in that, The device includes: The composite flooding experimental module is used to conduct composite flooding experiments on different lithologies, mineralization, and pore structures under formation conditions to obtain the variation law of the four reservoir properties in composite flooding water-flooded layers. The identification model building module is used to analyze the changing patterns of the four properties of reservoirs in composite flooded reservoirs and to establish a qualitative identification model for the degree of flooding. The variation law analysis module is used to perform stratification based on the qualitative identification model of the flooding degree, analyze the interpretation model of composite flooding pore saturation, clay content, and water production rate according to lithology, and establish a subdivision evaluation scheme and standard for composite flooding layer. The monitoring and evaluation module is used to monitor and evaluate the composite water flooding layer according to the subdivided evaluation scheme and standards of the composite water flooding layer, using static logging methods combined with dynamic parameters of casing logging, and to obtain composite water flooding layer monitoring and evaluation data. The distribution pattern determination module is used to construct a discrimination chart based on the monitoring and evaluation data of the composite flooding reservoir and the water flooding experiment, using data from open-hole wells and cased wells as well as regional geological data, and to determine the planar distribution pattern of the composite flooding reservoir water flooding layer based on the discrimination chart.

9. A reservoir water-flooded layer identification device, characterized in that, The device includes: Memory, used to store computer programs; A processor, configured to implement the steps of the reservoir water-flooded layer identification method as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the reservoir water-flooded layer identification method as described in any one of claims 1 to 7.

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