Fluid identification method, apparatus, processor, and machine-readable storage medium

Abstract

This invention provides a fluid identification method, apparatus, processor, and machine-readable storage medium, relating to the field of reservoir logging evaluation. The method includes: determining logging parameters of the test layer, adjacent standard water layer, and fluid type at multiple test depths of the tested formation; determining the invasion factor and oil-bearing discrimination index at each test depth; establishing a fluid cross-plot using the oil-bearing discrimination index, invasion factor, and fluid type at multiple test depths; determining the oil-water boundary based on the fluid cross-plot; determining the target layer logging parameters and adjacent standard water layer logging parameters at the depth to be tested; determining the invasion factor and oil-bearing discrimination index at the depth to be tested; and determining the fluid type at the depth to be tested using the fluid cross-plot, the oil-water boundary, and the oil-bearing discrimination index and invasion factor at the depth to be tested. This invention simplifies the fluid identification process and accurately identifies the fluid properties in underground reservoirs.

Description

Technical Field

[0001] This invention relates to the field of reservoir logging evaluation technology, specifically to a fluid identification method, a fluid identification device, a processor, and a machine-readable storage medium. Background Technology

[0002] Fluid property identification is crucial for oilfield exploration and development. In my country's low-permeability tight sandstone reservoirs, low-contrast oil reservoirs exhibit diverse genesis, controlled by reservoir formation and diagenetic conditions. Existing exploration and development of low-contrast oil reservoirs reveals that their formation mechanisms are often controlled by multiple factors, which can be categorized into external and internal factors. External factors mainly include mud intrusion and limited detection range of logging instruments; internal factors primarily include differences in formation water salinity, high bound water saturation, reservoir filling degree, and complex pore structure. However, as oilfield exploration and development deepen, single-gene low-contrast oil reservoirs are becoming increasingly rare, while multi-factor composite low-contrast oil reservoirs are gradually increasing, posing a significant challenge to logging identification.

[0003] Currently, domestic and international methods for identifying fluid properties in low-contrast oil reservoirs mainly include well logging curve overlap methods, fluid identification methods based on imaging logging data, and some classic optimization algorithms. Among these, the well logging curve overlap method, under certain criteria, determines fluid properties based on the size of the envelope area by overlapping well logging curves. This is a qualitative analysis method, typically only able to determine the criteria for distinguishing between oil and water layers. For low-contrast oil reservoirs with complex origins, the resolution of well logging curve overlap methods for fluid property identification is relatively limited. Fluid identification methods based on imaging logging data currently mainly include nuclear magnetic resonance (NMR) logging difference spectrum methods, NMR logging shift spectrum methods, and array acoustic logging acoustic parameter discrimination methods. These methods have good identification effects for low-contrast oil-water layers, but they are costly, have relatively complex processing and interpretation processes, and most old oilfields have limited imaging data, which to some extent limits the application of fluid identification methods based on imaging logging data. Optimization algorithms include artificial neural network methods, support vector machines, and fuzzy clustering methods. The key to their application is that they require a large number of training samples that can reflect the differences in the properties of different fluids as input, and the number of training samples with different fluid properties should be roughly the same to ensure the accuracy and reliability of the prediction model results. However, this method lacks theoretical basis. Summary of the Invention

[0004] To address the technical problems of complex fluid identification processes, limited applicability, and poor identification accuracy in existing technologies, this invention provides a fluid identification method, a fluid identification device, a processor, and a machine-readable storage medium. This fluid identification method simplifies the fluid identification process, accurately identifies the properties of fluids in underground reservoirs, enhances universality, effectively improves the success rate of oil and gas exploration, guides the formulation of oilfield development plans, and maximizes oil and gas extraction efficiency and economic benefits, thereby promoting the effective utilization and development of energy resources.

[0005] To achieve the above objectives, a first aspect of the present invention provides a fluid identification method, comprising: determining logging parameters of the detection layer at each detection depth of a test formation, logging parameters of adjacent standard water layers, and fluid type; determining an invasion factor at each detection depth using the logging parameters of the detection layer at each detection depth; and determining an oil-bearing discrimination index at each detection depth using the logging parameters of the detection layer at each detection depth and the logging parameters of adjacent standard water layers; wherein, the oil-bearing discrimination index represents oil-bearing properties; and the invasion factor represents the resistivity of the deep invasion portion and the resistivity of the shallow portion. The process involves: 1) establishing a fluid cross-plot using multiple detection depths for oil-bearing discrimination indices, invasion factors, and fluid types; 2) determining the oil-water layer boundary based on the fluid cross-plot; 3) determining the target layer logging parameters and adjacent standard water layer logging parameters for the depth to be measured; 4) determining the invasion factor for the depth to be measured using the target layer logging parameters; 5) determining the oil-bearing discrimination index for the depth to be measured using the fluid cross-plot, the oil-water layer boundary, and the oil-bearing discrimination index and invasion factor for the depth to be measured; and 6) determining the fluid type for the depth to be measured using the fluid cross-plot, the oil-water layer boundary, and the oil-bearing discrimination index and invasion factor.

[0006] Furthermore, the logging parameters of the detection layer include: the induced resistivity of the detection layer array, the porosity of the detection layer, and the relative amplitude of the spontaneous potential of the detection layer; wherein, the induced resistivity of the detection layer array includes: the induced resistivity of the AT90 array, the induced resistivity of the AT60 array, the induced resistivity of the AT30 array, the induced resistivity of the AT20 array, and the induced resistivity of the AT10 array.

[0007] Furthermore, the logging parameters of the adjacent standard aquifer include: the resistivity of the adjacent standard aquifer, the porosity of the adjacent standard aquifer, and the relative amplitude of the spontaneous potential of the adjacent standard aquifer.

[0008] Furthermore, the oil content discrimination index for each detection depth is determined in the following way: ; Where P is the oil content discrimination index, AT90 is the induced resistivity of the AT90 array in the detection layer, in Ω·m; RT w φ represents the resistivity of the adjacent standard water layer, in Ω·m; φ represents the porosity of the test layer, in %; φw ΔSP represents the porosity of the adjacent standard aquifer, in %; ΔSP represents the relative amplitude of the spontaneous potential of the detection layer, in mV. w The relative amplitude of the spontaneous potential of the adjacent standard water layer is expressed in mV.

[0009] Furthermore, the invasive factor at each detection depth is determined as follows: ; Where D is the intrusion factor; AT90 is the resistivity of the AT90 array of the detection layer; AT60 is the resistivity of the AT60 array of the detection layer; AT30 is the resistivity of the AT30 array of the detection layer; AT20 is the resistivity of the AT20 array of the detection layer; and AT10 is the resistivity of the AT10 array of the detection layer.

[0010] Furthermore, the step of establishing a fluid cross-plot using oil-containing discrimination indexes, intrusion factors, and fluid types at multiple detection depths includes: establishing an initial cross-plot with the oil-containing discrimination index as the horizontal axis and the intrusion factor as the vertical axis; and projecting the oil-containing discrimination indexes and intrusion factors at multiple detection depths onto the initial cross-plot according to the fluid type to establish the fluid cross-plot.

[0011] Furthermore, the method also includes: determining the total hydrocarbon parameters at multiple detection depths of the test formation; and establishing a fluid cross-plot using the oil-bearing discrimination index, intrusion factor, total hydrocarbon parameters, and fluid type at multiple detection depths.

[0012] Furthermore, the step of establishing a fluid cross-plot using oil-bearing discrimination index, invasion factor, total hydrocarbon parameters, and fluid type at multiple detection depths includes: establishing an initial cross-plot using the product of oil-bearing discrimination index and total hydrocarbon parameters as the horizontal axis and the invasion factor as the vertical axis; and plotting the product of oil-bearing discrimination index and total hydrocarbon parameters at multiple detection depths and the invasion factor into the initial cross-plot according to the fluid type to establish the fluid cross-plot.

[0013] Furthermore, the method also includes: determining the total hydrocarbon parameters of the depth to be measured; and determining the fluid type of the depth to be measured using the fluid cross-plot, the oil-water layer boundary, and the oil-bearing discrimination index, intrusion factor, and total hydrocarbon parameters of the depth to be measured.

[0014] A second aspect of the present invention provides a fluid identification device, the fluid identification device comprising: a determination module, configured to determine logging parameters of the detection layer at each detection depth of a test formation, logging parameters of adjacent standard water layers, and fluid type at multiple detection depths, and to determine the invasion factor at each detection depth using the logging parameters of the detection layer at each detection depth, and to determine the oil-bearing discrimination index at each detection depth using the logging parameters of the detection layer at each detection depth and the logging parameters of adjacent standard water layers; wherein, the oil-bearing discrimination index represents oil-bearing properties; the invasion factor represents the ratio of resistivity of the deep invasion portion to the resistivity of the shallow portion; and a map creation module, configured to utilize multiple... A fluid cross-plot is established based on the oil-bearing discrimination index, invasion factor, and fluid type at each detection depth, and the oil-water layer boundary is determined based on the fluid cross-plot. A depth parameter determination module is used to determine the target layer logging parameters and adjacent standard water layer logging parameters at the depth to be measured, and to determine the invasion factor and oil-bearing discrimination index at the depth to be measured using the target layer logging parameters. A fluid type determination module is used to determine the fluid type at the depth to be measured using the fluid cross-plot, the oil-water layer boundary, and the oil-bearing discrimination index and invasion factor at the depth to be measured.

[0015] A third aspect of the present invention provides a processor configured to perform the fluid recognition method described above.

[0016] A fourth aspect of the present invention provides a machine-readable storage medium storing instructions that, when executed by a processor, configure the processor to perform the fluid identification method described above.

[0017] The present invention has at least the following technical effects through the technical solution provided by the present invention: The fluid identification method of this invention first determines the logging parameters of the detection layer, the logging parameters of the adjacent standard water layer, and the fluid type at multiple detection depths of the oil-testing formation. It then uses the logging parameters of the detection layer at each detection depth to determine the invasion factor for that depth, and uses the logging parameters of the detection layer and the logging parameters of the adjacent standard water layer at each detection depth to determine the oil-bearing discrimination index for that depth. Next, it establishes a fluid cross-plot using the oil-bearing discrimination index, invasion factor, and fluid type at multiple detection depths, and determines the oil-water layer boundary based on the fluid cross-plot. Then, it determines the logging parameters of the target layer and the logging parameters of the adjacent standard water layer at the depth to be tested, and uses the logging parameters of the target layer at the depth to be tested to determine the invasion factor for that depth, and uses the logging parameters of the target layer at the depth to be tested to determine the oil-bearing discrimination index for that depth. Finally, it uses the fluid cross-plot, the oil-water layer boundary, and the oil-bearing discrimination index and invasion factor at the depth to be tested to determine the fluid type for that depth. The fluid identification method provided by the present invention can simplify the fluid identification process, accurately identify the fluid properties in underground reservoirs, enhance universality, effectively improve the success rate of oil and gas exploration, guide the formulation of oilfield development plans, maximize the efficiency and economic benefits of oil and gas extraction, and thus promote the effective utilization and development of energy resources.

[0018] Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0019] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings: The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings: Figure 1 A flowchart of the fluid identification method provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the fluid intersection map established in the fluid identification method provided in the embodiments of the present invention; Figure 3 This is a schematic diagram illustrating the projection of detection parameters from a verification well onto a fluid cross-section chart in the fluid identification method provided in this embodiment of the invention. Figure 4 This is a diagram showing the fluid identification results of a verification well in the fluid identification method provided in this embodiment of the invention. Figure 5 This is a schematic diagram of a fluid identification device provided in an embodiment of the present invention. Detailed Implementation

[0020] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present invention.

[0021] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0022] In this invention, unless otherwise stated, directional terms such as "upper," "lower," "top," and "bottom" are generally used to describe the relative positions of components in relation to the directions shown in the accompanying drawings or in relation to the vertical, perpendicular, or gravitational directions.

[0023] As described in the background section, existing semiconductor structures have poor performance. This will be explained in detail below with reference to the accompanying drawings.

[0024] Please refer to Figure 1 The first aspect of this invention provides a fluid identification method, which includes: S101: determining the logging parameters of the detection layer, the logging parameters of the adjacent standard water layer, and the fluid type at each detection depth of a test formation; determining the invasion factor at each detection depth using the logging parameters of the detection layer; and determining the oil-bearing discrimination index at each detection depth using the logging parameters of the detection layer and the logging parameters of the adjacent standard water layer; wherein, the oil-bearing discrimination index represents oil content; and the invasion factor represents the ratio of resistivity in the deep intrusion to resistivity in the shallow intrusion; S10 2: Establish a fluid cross-plot using oil-bearing discrimination index, invasion factor, and fluid type at multiple detection depths, and determine the oil-water layer boundary based on the fluid cross-plot; S103: Determine the target layer logging parameters and adjacent standard water layer logging parameters at the depth to be measured, and determine the invasion factor at the depth to be measured using the target layer logging parameters, and determine the oil-bearing discrimination index at the depth to be measured using the target layer logging parameters; S104: Determine the fluid type at the depth to be measured using the fluid cross-plot, the oil-water layer boundary, and the oil-bearing discrimination index and invasion factor at the depth to be measured.

[0025] Specifically, step S101 is first executed: the logging parameters of the detection layer, the logging parameters of the adjacent standard water layer, and the fluid type of each detection depth of the oil-testing formation are determined, and the invasion factor of the detection depth is determined using the logging parameters of the detection layer at each detection depth, and the oil-bearing discrimination index of the detection depth is determined using the logging parameters of the detection layer at each detection depth and the logging parameters of the adjacent standard water layer; wherein, the oil-bearing discrimination index represents the oil-bearing property; the invasion factor represents the ratio of the resistivity of the deep invasion to the resistivity of the shallow invasion.

[0026] Furthermore, the logging parameters of the detection layer include: the induced resistivity of the detection layer array, the porosity of the detection layer, and the relative amplitude of the spontaneous potential of the detection layer; wherein, the induced resistivity of the detection layer array includes: the induced resistivity of the AT90 array, the induced resistivity of the AT60 array, the induced resistivity of the AT30 array, the induced resistivity of the AT20 array, and the induced resistivity of the AT10 array.

[0027] Furthermore, the logging parameters of the adjacent standard aquifer include: the resistivity of the adjacent standard aquifer, the porosity of the adjacent standard aquifer, and the relative amplitude of the spontaneous potential of the adjacent standard aquifer.

[0028] Furthermore, the oil content discrimination index for each detection depth is determined in the following way: ; Where P is the oil content discrimination index, AT90 is the induced resistivity of the AT90 array in the detection layer, in Ω·m; RT w φ represents the resistivity of the adjacent standard water layer, in Ω·m; φ represents the porosity of the test layer, in %; φ w ΔSP represents the porosity of the adjacent standard aquifer, in %; ΔSP represents the relative amplitude of the spontaneous potential of the detection layer, in mV. w The relative amplitude of the spontaneous potential of the adjacent standard water layer is expressed in mV.

[0029] Furthermore, the invasive factor at each detection depth is determined as follows: ; Where D is the intrusion factor; AT90 is the resistivity of the AT90 array of the detection layer; AT60 is the resistivity of the AT60 array of the detection layer; AT30 is the resistivity of the AT30 array of the detection layer; AT20 is the resistivity of the AT20 array of the detection layer; and AT10 is the resistivity of the AT10 array of the detection layer.

[0030] Specifically, in this embodiment of the invention, the testing formation is first tested to determine the logging parameters of the testing layer and the adjacent standard water layer at multiple testing depths. Then, the fluid type at each testing depth is determined. The logging parameters of the testing layer include, but are not limited to: the array resistivity of the testing layer, the porosity φ of the testing layer, and the relative amplitude of the spontaneous potential ΔSP of the testing layer. The array resistivity of the testing layer includes: the array resistivity of AT90, AT60, AT30, AT20, and AT10. The logging parameters of the adjacent standard water layer include, but are not limited to: the resistivity RT of the adjacent standard water layer. w Porosity φ of adjacent standard aquifer wThe relative amplitude of the spontaneous potential ΔSP of the adjacent standard water layer w .

[0031] Then, the invasion factor D for each detection depth is determined using the logging parameters of the detection layer at each detection depth. ; Where D is the intrusion factor; AT90 is the induced resistivity of the AT90 array of the detection layer; AT60 is the induced resistivity of the AT60 array of the detection layer; AT30 is the induced resistivity of the AT30 array of the detection layer; AT20 is the induced resistivity of the AT20 array of the detection layer; and AT10 is the induced resistivity of the AT10 array of the detection layer. The intrusion factor represents the ratio of the resistivity of the deep intrusion to the resistivity of the shallow intrusion, characterizing the mud intrusion factor.

[0032] The oil-bearing discrimination index P at each detection depth is determined using the logging parameters of the detection layer and the logging parameters of the adjacent standard water layer. ; Where P is the oil content discrimination index, AT90 is the induced resistivity of the AT90 array in the detection layer, in Ω·m; RT w φ represents the resistivity of the adjacent standard water layer, in Ω·m; φ represents the porosity of the test layer, in %; φ w ΔSP represents the porosity of the adjacent standard aquifer, in %; ΔSP represents the relative amplitude of the spontaneous potential of the detection layer, in mV. w The relative amplitude of the spontaneous potential of the adjacent standard water layer is expressed in mV. The oil-bearing discrimination index indicates oil content. This application comprehensively considers various causes of low-contrast oil layers and introduces an oil-bearing discrimination index to weaken the influence of physical properties, pore structure, and formation water salinity on the resistivity curve characteristics.

[0033] Next, step S102 is performed: a fluid cross-plot is established using multiple detection depths of oil-bearing discrimination index, intrusion factor and fluid type, and the oil-water layer boundary is determined based on the fluid cross-plot.

[0034] Furthermore, the step of establishing a fluid cross-plot using oil-containing discrimination indexes, intrusion factors, and fluid types at multiple detection depths includes: establishing an initial cross-plot with the oil-containing discrimination index as the horizontal axis and the intrusion factor as the vertical axis; and projecting the oil-containing discrimination indexes and intrusion factors at multiple detection depths onto the initial cross-plot according to the fluid type to establish the fluid cross-plot.

[0035] Furthermore, the method also includes: determining the total hydrocarbon parameters at multiple detection depths of the test formation; and establishing a fluid cross-plot using the oil-bearing discrimination index, intrusion factor, total hydrocarbon parameters, and fluid type at multiple detection depths.

[0036] Furthermore, the step of establishing a fluid cross-plot using oil-bearing discrimination index, invasion factor, total hydrocarbon parameters, and fluid type at multiple detection depths includes: establishing an initial cross-plot using the product of oil-bearing discrimination index and total hydrocarbon parameters as the horizontal axis and the invasion factor as the vertical axis; and plotting the product of oil-bearing discrimination index and total hydrocarbon parameters at multiple detection depths and the invasion factor into the initial cross-plot according to the fluid type to establish the fluid cross-plot.

[0037] Specifically, in this embodiment of the invention, a rectangular coordinate system is first established with the oil-bearing discrimination index P as the horizontal axis and the intrusion factor D as the vertical axis to obtain an initial cross-plot. Then, according to the fluid type, the oil-bearing discrimination index and intrusion factor at multiple detection depths are projected onto the initial cross-plot to establish a fluid cross-plot. In this embodiment, the fluid types include oil layers, oil-water co-layers, oil-bearing water layers, and water layers. Based on the projection of each fluid type on the fluid cross-plot, the boundaries between oil and water layers are delineated.

[0038] In another possible implementation, total hydrocarbon parameters are added to determine the fluid type, thereby improving fluid identification accuracy. When testing the oil-bearing formation, total hydrocarbon parameters are determined at multiple detection depths. After determining the oil-bearing discrimination index and invasion factor at multiple detection depths, the oil-bearing discrimination index is multiplied by the total hydrocarbon parameters, and the result is plotted on the x-axis with the invasion factor on the y-axis to establish a Cartesian coordinate system, yielding an initial fluid cross-plot. The product of the oil-bearing discrimination index and the total hydrocarbon parameters at multiple detection depths, along with the invasion factor, is then plotted onto the initial cross-plot according to fluid type, thus establishing the fluid cross-plot. Please refer to [reference needed]. Figure 2 In this embodiment, the fluid types include oil layer, oil-water co-layer, oil-water layer and water layer. The boundaries of the oil-water layer are defined according to the projection of each fluid type on the fluid intersection chart. Figure 2 The solid black lines in the diagram represent the defined boundaries between oil and water layers: the boundary between an oil layer and an oil-water co-containment layer is defined as an invasion factor D > 0.7 and an oil-bearing discrimination index P*total hydrocarbons QT > 0.6; the boundary between an oil-bearing water layer and a water layer is defined as an invasion factor D ≤ 0.7 and an oil-bearing discrimination index P*total hydrocarbons QT ≤ 0.6.

[0039] The total hydrocarbon parameter represents the oil content of a fluid. Multiplying the oil content discrimination index by the total hydrocarbon parameter can amplify the oil content of the fluid, making the boundary between oil and water layers more obvious, better distinguishing between water and oil, more accurately identifying the fluid properties in underground reservoirs, and improving identification accuracy.

[0040] Next, proceed to step S103: determine the logging parameters of the target layer and the adjacent standard water layer at the depth to be measured, and use the logging parameters of the target layer at the depth to be measured to determine the invasion factor at the depth to be measured, and use the logging parameters of the target layer at the depth to be measured to determine the oil-bearing discrimination index at the depth to be measured.

[0041] Finally, step S104 is executed: using the fluid intersection chart, the oil-water layer boundary, and the oil-bearing discrimination index and intrusion factor of the depth to be measured, the fluid type of the depth to be measured is determined.

[0042] Furthermore, the method also includes: determining the total hydrocarbon parameters of the depth to be measured; and determining the fluid type of the depth to be measured using the fluid cross-plot, the oil-water layer boundary, and the oil-bearing discrimination index, intrusion factor, and total hydrocarbon parameters of the depth to be measured.

[0043] Specifically, in this embodiment of the invention, when identifying the fluid type at the depth to be measured, the logging parameters of the target layer and the logging parameters of the adjacent standard water layer at the depth to be measured are determined. Following the same method as determining the oil-bearing discrimination index and invasion factor at the depth to be measured, the invasion factor at the depth to be measured is determined using the logging parameters of the target layer, and the oil-bearing discrimination index at the depth to be measured is determined using the logging parameters of the target layer. The oil-bearing discrimination index and invasion factor at the depth to be measured are plotted on the fluid cross-plot established by the above method, and the fluid type at the depth to be measured is determined based on the location of the plotted points.

[0044] In another possible implementation, when adding full hydrocarbon parameters to determine the fluid type, after establishing a fluid cross-plot including full hydrocarbon parameters and determining the intrusion factor and oil content discrimination index of the depth to be measured, the product of the oil content discrimination index of the depth to be measured and the full hydrocarbon parameters and the intrusion factor are plotted on the fluid cross-plot including full hydrocarbon parameters. Based on the position of the plotted points, the fluid type of the depth to be measured is determined.

[0045] In this embodiment, the above method was verified. One oil well to be identified in the study area was selected, and the oil-bearing discrimination index P, invasion factor D, and oil-bearing discrimination index P*total hydrocarbon QT of the oil well to be identified were calculated, which are respectively Figure 4 The calculation results for the eleventh, twelfth, and thirteenth channels show that P and D for layer 46 (target layer) are 1.37 and 0.83 respectively, and P*QT is 8.1. The points for layer 46 are then projected... Figure 2 In the fluid intersection diagram, we obtain Figure 3 The fluid cross-section chart shown indicates that layer 46 of this well is located in the oil-bearing zone, and layer 46 is interpreted as an oil-bearing layer. A test was conducted on layer 46, and the results showed a daily oil production of 118.66 tons and a daily water production of 0 cubic meters per second. 3 This confirms that layer 46 is an oil layer, thus demonstrating the reliability of the invention and its applicability in low-contrast fluid property identification.

[0046] A comprehensive analysis of the effects of formation water salinity, bound water saturation, reservoir properties, and drilling fluid invasion on reservoir resistivity suggests that, under similar salinity and bound water saturation conditions, greater porosity results in a larger reservoir water volume, higher permeability, better reservoir connectivity, a more developed reservoir conductive network, and lower resistivity. In the context of high salinity and low oil saturation, favorable reservoir properties facilitate communication between mobile and bound water within the reservoir pore space, forming a robust reservoir conductive network, leading to generally lower resistivity. Simultaneously, the invasion of freshwater slurry significantly increases the resistivity of the water layer, further reducing the rate of increase in oil layer resistivity. Therefore, the primary controlling factor for oil-water layer identification is the reservoir properties under conditions of high formation water salinity and low oil saturation, which vary considerably. Freshwater slurry invasion is the main interfering factor affecting the oil-water resistivity boundary in the study area. Cross-plots of single physical properties are insufficient for identifying fluid properties. To mitigate the influence of lithology, physical properties, and formation water salinity on resistivity, an oil-bearing index was constructed, and an intrusion factor was constructed to consider the impact of mud intrusion on resistivity.

[0047] Please refer to Figure 5 The second aspect of the present invention provides a fluid identification device, the fluid identification device comprising: a determination module, configured to determine logging parameters of the detection layer at each detection depth of a test formation, logging parameters of adjacent standard water layers, and fluid type at multiple detection depths, and to determine the invasion factor at each detection depth using the logging parameters of the detection layer at each detection depth, and to determine the oil-bearing discrimination index at each detection depth using the logging parameters of the detection layer at each detection depth and the logging parameters of adjacent standard water layers; wherein, the oil-bearing discrimination index represents oil-bearing properties; the invasion factor represents the ratio of resistivity of the deep invasion portion to the resistivity of the shallow portion; and a map creation module, configured to utilize multiple... A fluid cross-plot is established based on the oil-bearing discrimination index, invasion factor, and fluid type at each detection depth, and the oil-water layer boundary is determined based on the fluid cross-plot. A depth parameter determination module is used to determine the target layer logging parameters and adjacent standard water layer logging parameters at the depth to be measured, and to determine the invasion factor and oil-bearing discrimination index at the depth to be measured using the target layer logging parameters. A fluid type determination module is used to determine the fluid type at the depth to be measured using the fluid cross-plot, the oil-water layer boundary, and the oil-bearing discrimination index and invasion factor at the depth to be measured.

[0048] A third aspect of the present invention provides a processor configured to perform the fluid recognition method described above.

[0049] A fourth aspect of the present invention provides a machine-readable storage medium storing instructions that, when executed by a processor, configure the processor to perform the fluid identification method described above.

[0050] The preferred embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the specific details of the above embodiments. Within the scope of the technical concept of the present invention, various simple modifications can be made to the technical solution of the present invention, and these simple modifications all fall within the protection scope of the present invention.

[0051] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present invention will not describe the various possible combinations separately.

[0052] Furthermore, various different embodiments of the present invention can be combined in any way, as long as they do not violate the spirit of the present invention, they should also be regarded as the content disclosed by the present invention.

Claims

1. A fluid identification method, characterized in that, The fluid identification method includes: The logging parameters of the detection layer, the logging parameters of the adjacent standard water layer, and the fluid type at multiple detection depths of the oil-testing formation are determined. The invasion factor at each detection depth is determined using the logging parameters of the detection layer at each detection depth and the logging parameters of the adjacent standard water layer. The oil-bearing discrimination index at each detection depth is determined using the logging parameters of the detection layer at each detection depth and the logging parameters of the adjacent standard water layer. Among them, the oil-bearing discrimination index represents the oil-bearing property; the invasion factor represents the ratio of the resistivity of the deep invasion to the resistivity of the shallow invasion. A fluid cross-plot is established using oil-bearing discrimination indexes, intrusion factors, and fluid types at multiple detection depths, and the oil-water layer boundary is determined based on the fluid cross-plot. Determine the logging parameters of the target layer and the adjacent standard water layer at the depth to be measured, and use the logging parameters of the target layer at the depth to be measured to determine the invasion factor at the depth to be measured, and use the logging parameters of the target layer at the depth to be measured to determine the oil-bearing discrimination index at the depth to be measured. The fluid type at the depth to be measured is determined by using the fluid cross-section chart, the oil-water layer boundary, and the oil-bearing discrimination index and intrusion factor at the depth to be measured.

2. The fluid identification method according to claim 1, characterized in that, The logging parameters for the detection layer include: the induced resistivity of the detection layer array, the porosity of the detection layer, and the relative amplitude of the spontaneous potential of the detection layer; wherein, the induced resistivity of the detection layer array includes: the induced resistivity of the AT90 array, the induced resistivity of the AT60 array, the induced resistivity of the AT30 array, the induced resistivity of the AT20 array, and the induced resistivity of the AT10 array.

3. The fluid identification method according to claim 2, characterized in that, The logging parameters of the adjacent standard aquifer include: resistivity, porosity, and relative amplitude of spontaneous potential of the adjacent standard aquifer.

4. The fluid identification method according to claim 3, characterized in that, The oil content discrimination index for each detection depth is determined in the following way: ； Where P is the oil content discrimination index, AT90 is the induced resistivity of the AT90 array in the detection layer, in Ω·m; RT w φ represents the resistivity of the adjacent standard water layer, in Ω·m; φ represents the porosity of the test layer, in %; φ w ΔSP represents the porosity of the adjacent standard aquifer, in %; ΔSP represents the relative amplitude of the spontaneous potential of the detection layer, in mV. w The relative amplitude of the spontaneous potential of the adjacent standard water layer is expressed in mV.

5. The fluid identification method according to claim 4, characterized in that, The invasive factor at each detection depth is determined as follows: ； Where D is the intrusion factor; AT90 is the resistivity of the AT90 array of the detection layer; AT60 is the resistivity of the AT60 array of the detection layer; AT30 is the resistivity of the AT30 array of the detection layer; AT20 is the resistivity of the AT20 array of the detection layer; and AT10 is the resistivity of the AT10 array of the detection layer.

6. The fluid identification method according to claim 1, characterized in that, The process of establishing a fluid cross-plot using oil-bearing discrimination indices, intrusion factors, and fluid types at multiple detection depths includes: An initial cross plot was established using the oil content discrimination index as the horizontal axis and the intrusion factor as the vertical axis. According to the fluid type, the oil-bearing discrimination index and intrusion factor at multiple detection depths are plotted onto the initial cross-plot to establish the fluid cross-plot.

7. The fluid identification method according to claim 1, characterized in that, The method further includes: Determine the total hydrocarbon parameters at multiple detection depths in the oil testing formation; A fluid cross-plot was created using oil-bearing discrimination index, intrusion factor, total hydrocarbon parameters, and fluid type at multiple detection depths.

8. The fluid identification method according to claim 7, characterized in that, The process of establishing a fluid cross-plot using oil-bearing discrimination indices, intrusion factors, total hydrocarbon parameters, and fluid types at multiple detection depths includes: An initial cross plot was established using the product of the oil content discrimination index and the total hydrocarbon parameter as the horizontal axis and the intrusion factor as the vertical axis. According to the fluid type, the product of the oil-bearing discrimination index at multiple detection depths and the total hydrocarbon parameter, along with the intrusion factor, are plotted onto the initial cross-plot to establish the fluid cross-plot.

9. The fluid identification method according to claim 8, characterized in that, The method further includes: Determine the total hydrocarbon parameters at the depth to be measured; The fluid type at the depth to be measured is determined by using the fluid cross-section chart, the oil-water layer boundary, and the oil-bearing discrimination index, intrusion factor, and total hydrocarbon parameters of the depth to be measured.

10. A fluid identification device, characterized in that, The fluid identification device includes: The determination module is used to determine the logging parameters of the detection layer, the logging parameters of the adjacent standard water layer, and the fluid type at multiple detection depths of the oil-testing formation. It then uses the logging parameters of the detection layer at each detection depth to determine the invasion factor at that depth, and uses the logging parameters of the detection layer and the logging parameters of the adjacent standard water layer at each detection depth to determine the oil-bearing discrimination index at that depth. The oil-bearing discrimination index indicates oil content; the invasion factor represents the ratio of resistivity in the deep intrusion area to resistivity in the shallow intrusion area. The chart creation module is used to create a fluid cross-hatching chart using oil-bearing discrimination index, intrusion factor and fluid type at multiple detection depths, and to determine the oil-water layer boundary based on the fluid cross-hatching chart. The module for determining the depth parameters is used to determine the logging parameters of the target layer and the logging parameters of the adjacent standard water layer at the depth to be measured. It also uses the logging parameters of the target layer to determine the invasion factor at the depth to be measured and the logging parameters of the target layer to determine the oil-bearing discrimination index at the depth to be measured. The fluid type determination module is used to determine the fluid type at the depth to be measured by utilizing the fluid intersection chart, the oil-water layer boundary, and the oil-bearing discrimination index and intrusion factor at the depth to be measured.

11. A processor, characterized in that, It is configured to perform the fluid identification method according to any one of claims 1 to 9.

12. A machine-readable storage medium storing instructions thereon, characterized in that, When executed by a processor, the instruction causes the processor to be configured to perform the fluid identification method according to any one of claims 1 to 9.

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