Well bottom reservoir oil and gas phase fluid property identification method, device, equipment and medium

Abstract

The application discloses a kind of well bottom reservoir oil and gas phase state fluid property identification method, device, equipment and medium, it is related to oil well exploration field, the method includes: collecting the relevant data of wireline formation testing in pumping operation, form data set;Construct wireline formation testing three-dimensional seepage numerical simulation model, the mass conservation equation in it is dispersed and solved, obtain pressure distribution field and water saturation distribution field;According to pressure distribution field, water saturation distribution field and probe node fluid spherical flow characteristics, establish probe suction fluid hydrocarbon content calculation model;Using data set and probe suction fluid hydrocarbon content calculation model, simulate and calculate the hydrocarbon content curve of the same type strata oil and gas classification, construct cluster chart;The hydrocarbon phase breakthrough time of actual formation testing operation of the same type strata to be processed is compared with cluster chart, and the fluid property of the strata to be processed is identified.The application can conveniently and accurately identify the fluid property of the strata to be processed.

Description

Technical Field

[0001] This invention relates to the field of oil and gas field exploration and development technology, specifically to a method, device, equipment, and medium for identifying the phase fluid properties of oil and gas in bottom-hole reservoirs. Background Technology

[0002] Cable-guided formation testing is a key logging technology in oil and gas exploration and development. It involves lowering specialized testing instruments into the well via a cable to conduct in-situ testing of the formation in the target layer, rapidly acquiring dynamic pressure data and other information to provide crucial data for reservoir evaluation, production prediction, and development decisions. This invention aims to effectively identify the properties of underground reservoir fluids based on hydrocarbon phase breakthrough time obtained through cable-guided formation testing, providing a new approach to bottom-hole reservoir oil and gas phase identification. Summary of the Invention

[0003] In view of the above problems, the present invention is proposed to provide a method, apparatus, equipment and medium for identifying the phase fluid properties of oil and gas in well bottom reservoirs that overcomes or at least partially solves the above problems.

[0004] According to one aspect of the embodiments of this application, a method for identifying the phase fluid properties of oil and gas in bottom-hole reservoirs is provided, the method comprising:

[0005] Collect relevant data from cable strata testing during pumping operations to form a dataset;

[0006] A three-dimensional numerical simulation model of seepage in cable strata testing was constructed. The mass conservation equation in the three-dimensional numerical simulation model of seepage in cable strata testing was discretized and solved to obtain the pressure distribution field and the water saturation distribution field.

[0007] Based on the pressure distribution field, water saturation distribution field, and the characteristics of spherical flow of fluid at the probe node, a calculation model for the hydrocarbon content of the probe suction fluid in cable strata testing is established.

[0008] Using datasets and a probe suction port fluid hydrocarbon content calculation model, we simulated and calculated hydrocarbon content curves for hydrocarbon classification of the same type of formation, and constructed a clustering chart for identifying the fluid properties of hydrocarbon reservoirs.

[0009] By comparing the hydrocarbon phase breakthrough time of actual formation testing operations of the same type of formation to be treated with the clustering chart, the fluid properties of the formation to be treated can be identified.

[0010] Furthermore, the three-dimensional seepage numerical simulation model for cable formation testing is used to simulate the near-wellbore reservoir water saturation and formation pressure distribution during the pumping process;

[0011] The three-dimensional seepage numerical simulation model for cable stratum testing includes: model assumptions, mass conservation equations, boundary conditions, initial conditions, and auxiliary equations;

[0012] The calculation model for the hydrocarbon content of the probe suction fluid includes: fluid water content equation, fluid water flow rate equation, fluid hydrocarbon flow rate equation, and fluid hydrocarbon content equation.

[0013] Furthermore, the mass conservation equation in the three-dimensional seepage numerical simulation model for cable strata testing is discretized and solved to obtain the pressure distribution field and water saturation distribution field, which further include:

[0014] The mass conservation equation was discretized using the finite volume method to obtain the pressure discretization equation and the water saturation discretization equation.

[0015] By using an iterative solution method that stabilizes the biconjugate gradient through matrix preprocessing, the pressure discrete equation and the water saturation discrete equation are solved to obtain the pressure distribution field and the water saturation distribution field.

[0016] Furthermore, using the dataset and the probe suction port fluid hydrocarbon content calculation model, the hydrocarbon content curves for classifying hydrocarbons in the same type of formation are simulated and calculated. A clustering map for identifying the fluid properties of hydrocarbon reservoirs is constructed, which further includes:

[0017] Using a dataset and a model for calculating the hydrocarbon content of fluid at the probe suction port, the hydrocarbon content curve at the suction port of the preset probe size is simulated and calculated under the same wellbore and pumping operation parameters for the same type of target formation. The corresponding hydrocarbon phase breakthrough time is determined based on the hydrocarbon content curve.

[0018] Based on the oil and gas types, hydrocarbon content curves, and hydrocarbon phase breakthrough times of similar target formations obtained from cable strata testing, sample data are generated to construct a sample set.

[0019] Based on the sample set, a clustering map is constructed using dynamic time warping and hierarchical clustering algorithms. The clustering map includes hydrocarbon content curves for hydrocarbon classification of the same type of formation and the boundaries of hydrocarbon content curves for hydrocarbon classification of the same type of formation.

[0020] Furthermore, based on the sample set, the clustering diagram constructed using dynamic time warping and hierarchical clustering algorithms further includes:

[0021] The same pumping operation time length is extracted from the hydrocarbon content curves of each sample data in the sample set and used as the sample curves.

[0022] Hierarchical clustering algorithm is used to form a single cluster using individual sample curves; the distance of each cluster is calculated by dynamic time warping algorithm, and a preset number of clusters with close distances are selected for merging. The distance strategy is updated by merging the clusters, and this step is repeated. During the clustering process, pruning operation is performed according to the preset pruning decision until the target cluster for oil and gas classification is obtained by merging.

[0023] The hydrocarbon content curves corresponding to the target clusters are projected onto the hydrocarbon content curve map to form a clustering chart. Based on the hydrocarbon content curves corresponding to the target clusters, the boundaries of hydrocarbon content curves for the same type of formation oil and gas classification are determined, and the boundaries of hydrocarbon content curves for the same type of formation oil and gas classification are marked on the clustering chart.

[0024] Furthermore, by comparing the hydrocarbon phase breakthrough times of actual formation testing operations of similar formations to be treated with clustering charts, the fluid properties of the formations to be treated were further identified, including:

[0025] Based on the hydrocarbon content curve boundaries of the same type of formation hydrocarbon classification in the clustering chart, the maximum breakthrough time of gas phase hydrocarbon content and the minimum breakthrough time of oil phase hydrocarbon content are extracted.

[0026] When the hydrocarbon phase breakthrough time is less than the maximum breakthrough time of the gaseous hydrocarbon content, the fluid properties of the formation to be treated are determined to be gaseous fluid.

[0027] When the hydrocarbon phase breakthrough time is greater than the minimum breakthrough time of the oil phase hydrocarbon content, the fluid properties of the formation to be treated are determined to be oil phase fluid.

[0028] When the hydrocarbon phase breakthrough time is greater than or equal to the maximum breakthrough time of gas phase hydrocarbon content and less than or equal to the minimum breakthrough time of oil phase hydrocarbon content, the fluid properties of the formation to be treated are determined to be oil-gas coexisting fluid.

[0029] According to another aspect of the embodiments of this application, a bottom-hole reservoir oil and gas phase fluid property identification device is provided, the device comprising:

[0030] The data acquisition module is suitable for collecting relevant data from cable strata testing during pumping operations to form a dataset.

[0031] The first construction module is suitable for constructing a three-dimensional seepage numerical simulation model for cable strata testing. It discretizes and solves the mass conservation equation in the three-dimensional seepage numerical simulation model for cable strata testing to obtain the pressure distribution field and the water saturation distribution field.

[0032] The second construction module is suitable for establishing a calculation model of the hydrocarbon content of the probe suction fluid for cable formation testing based on the pressure distribution field, water saturation distribution field, and the spherical flow characteristics of the probe node fluid.

[0033] The chart construction module is suitable for using datasets and probe suction port fluid hydrocarbon content calculation models to simulate and calculate hydrocarbon content curves for oil and gas classification of the same type of formation, and to construct cluster charts for oil and gas reservoir fluid property identification.

[0034] The identification module is suitable for comparing the hydrocarbon phase breakthrough time of actual formation testing operations of the same type of formation to be treated with the clustering chart to identify the fluid properties of the formation to be treated.

[0035] According to another aspect of the embodiments of this application, a computing device is provided, including: a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other through the communication bus;

[0036] The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the above-mentioned bottom-hole reservoir oil and gas phase fluid property identification method.

[0037] According to another aspect of the embodiments of this application, a computer storage medium is provided, which stores at least one executable instruction that causes a processor to perform operations corresponding to the above-described bottom-hole reservoir oil and gas phase fluid property identification method.

[0038] According to another aspect of the embodiments of this application, a computer program product is provided, including at least one executable instruction, which causes a processor to perform operations corresponding to the above-described bottom-hole reservoir oil and gas phase fluid property identification method.

[0039] According to the technical solution provided by this invention, a three-dimensional seepage numerical simulation model and a probe suction port fluid hydrocarbon content calculation model for cable formation testing are constructed. Through dynamic time warping algorithm and hierarchical clustering algorithm, a clustering chart for identifying the fluid properties of oil and gas reservoirs is constructed. Identification criteria for identifying the fluid properties of oil and gas reservoirs based on the hydrocarbon phase breakthrough time of actual formation testing operations are established. By comparing the hydrocarbon phase breakthrough time of actual formation testing operations of the same type of formation to be treated with the clustering chart, the fluid properties of the formation to be treated can be identified conveniently and accurately. This achieves the goal of identifying the fluid properties of bottom hole reservoirs based on hydrocarbon phase breakthrough time, providing a reliable solution and technical means for identifying the oil and gas phase fluid properties of underground reservoirs in cable formation testing.

[0040] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0041] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0042] Figure 1 A flowchart illustrating a method for identifying the phase fluid properties of oil and gas in a bottom-hole reservoir according to an embodiment of this application is shown.

[0043] Figure 2 The diagram illustrates the hydrocarbon content curves obtained from simulation and monitoring statistical calculations of pumping operations during cable formation testing. Figure 1 ;

[0044] Figure 3 A schematic diagram of a clustering chart is shown;

[0045] Figure 4 The diagram illustrates the hydrocarbon content curves obtained from simulation and monitoring statistical calculations of pumping operations during cable formation testing. Figure 2 ;

[0046] Figure 5 The diagram illustrates the hydrocarbon content curves obtained from simulation and monitoring statistical calculations of pumping operations during cable formation testing. Figure 3 ;

[0047] Figure 6 A structural block diagram of a bottom-hole reservoir oil and gas phase fluid property identification device according to an embodiment of this application is shown;

[0048] Figure 7 A schematic diagram of the structure of a computing device according to an embodiment of this application is shown. Detailed Implementation

[0049] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0050] Figure 1 A flowchart illustrating a method for identifying the phase-fluid properties of oil and gas in a bottom-hole reservoir according to an embodiment of this application is shown, as follows. Figure 1 As shown, the method includes the following steps:

[0051] Step S101: Collect relevant data from cable stratum testing during pumping operations to form a dataset.

[0052] This involves collecting data on the properties of different formations, wellbore, pumping, and fluids during cable formation testing and pumping operations. This data will form a dataset that provides the foundation for constructing a three-dimensional seepage numerical simulation model and performing fluid identification analysis for subsequent cable formation testing. Specifically, the dataset may include: a subset of formation property data for the near-wellbore target formation, a subset of wellbore property data for the near-wellbore target formation, a subset of pumping probe data from cable formation testing, and a subset of fluid property data for the near-wellbore target formation.

[0053] The near-well target formation data subset is based on the target formation where the well is located. It includes formation property data determined through well logging data analysis. The formation property data may specifically include formation depth, porosity, permeability, clay content, water saturation, lithology, rock compressibility, etc.

[0054] The wellbore property data subset for the near-wellbore target formation is based on the wellbore where the target formation is located. It includes wellbore property data from cable formation tests such as logging. The wellbore property data may specifically include wellbore radius, mud density, and the range of mud intrusion into the wellbore (e.g., the radius of the flushing zone, transition zone, and intrusion zone).

[0055] The subset of pumping probe data for cable strata testing includes pumping probe properties such as pumping speed, probe type, and suction port area.

[0056] The fluid property data subset of the near-well target formation is based on the fluids within the target formation where the well is located. It includes the collected fluid property data, which may specifically include the density, viscosity, volume factor, compressibility factor, and oil-water and gas-water phase permeability curves of hydrocarbon fluids such as oil and gas.

[0057] Step S102: Construct a three-dimensional seepage numerical simulation model for cable stratum testing, discretize and solve the mass conservation equation in the three-dimensional seepage numerical simulation model for cable stratum testing, and obtain the pressure distribution field and water saturation distribution field.

[0058] The three-dimensional numerical simulation model for cable formation testing is used to simulate the near-wellbore formation fluid flow process during pumping, specifically simulating the near-wellbore reservoir water saturation and formation pressure distribution during pumping. The three-dimensional numerical simulation model for cable formation testing includes: model assumptions, mass conservation equations, boundary conditions, initial conditions, and auxiliary equations.

[0059] Specifically, the model assumptions may include: the seepage is a three-dimensional radial flow; the seepage of the mixed fluid of formation oil, formation water and mud filtrate is considered; a black oil model is used; formation heterogeneity is considered; both incompressible and compressible fluids are supported; there is no diffusion or chemical reaction in the flow process (adsorption of mud on the well wall is not considered for the time being); the outer boundary supports constant pressure / closed boundary and the inner boundary supports constant fluid / constant pressure.

[0060] The integral form of the mass conservation equation is shown in equation (1):

[0061] (1)

[0062] In equation (1), y The category number represents the different fluid components, where o represents the formation hydrocarbon phase, and (w+m) represents the formation water phase and mud filtrate phase; Represents the flow velocity vector; Indicates the first y The flow velocity vector of the first fluid component; E represents the area; N represents the flow velocity vector of the second fluid component. y The source term of a fluid component; V represents volume; Porosity is represented by ; S represents the saturation of the fluid component. Indicates the first y The saturation degree of a fluid component; ρ represents the density of the fluid component; Indicates the first y The density of a fluid component. Wherein, the left-hand side of equation (1) represents the area component of the energy flux through area E and the density of the first fluid component. y The source term of the fluid component; the triple integral on the right side of the equation represents the rate of change of energy within volume V. Equation (1) represents the energy flux through area E and the first... y The sum of the source terms of a fluid component equals the rate of change of energy within volume V, describing the conservation relationship between the energy flux through area E, the source terms of the fluid component, and the rate of change of energy within volume V.

[0063] The initial conditions include the initial pressure distribution conditions and the initial fluid distribution conditions. The equation for the initial pressure distribution conditions is shown in equation (2), and the equation for the initial fluid distribution conditions is shown in equation (3).

[0064] (2)

[0065] (3)

[0066] Where P represents pressure; S represents fluid saturation; x represents the location of the distribution; and t represents time.

[0067] The boundary conditions include isobaric boundary conditions and isoliquid boundary conditions. The equation for the isobaric boundary condition is shown in equation (4), and the equation for the isoliquid boundary condition is shown in equation (5).

[0068] (4)

[0069] (5)

[0070] in, P Indicates pressure; q This indicates the amount of formation water, formation oil, and total flow rate of mud filtrate extraction. r Indicates the boundary radius; t Indicates time.

[0071] The auxiliary equations include the oil phase relative permeability equation, the water phase relative permeability equation, the oil phase viscosity equation, the oil phase volume coefficient equation, the oil phase density equation, and the formation fluid density equation. Specifically, the oil phase relative permeability equation is shown in equation (6), the water phase relative permeability equation is shown in equation (7), the oil phase viscosity equation is shown in equation (8), the oil phase volume coefficient equation is shown in equation (9), the oil phase density equation is shown in equation (10), and the formation fluid density equation is shown in equation (11).

[0072] (6)

[0073] (7)

[0074] (8)

[0075] (9)

[0076] (10)

[0077] (11)

[0078] in, Indicates the relative permeability of the oil phase; Indicates water saturation; Indicates the relative permeability of the aqueous phase; Indicates the viscosity of the oil phase fluid; P Indicates pressure; Indicates the oil phase volume coefficient; Indicates the density of the oil phase fluid; Indicates the density of the aqueous fluid; This indicates the density of the mud.

[0079] In step S102, the mass conservation equation is discretized using the finite volume method to obtain the pressure discretization equation and the water saturation discretization equation; the pressure discretization equation and the water saturation discretization equation are solved by the iterative solution method of matrix preprocessing to stabilize the double conjugate gradient, and the pressure distribution field and the water saturation distribution field are obtained.

[0080] Specifically, spatial discretization is performed using the finite volume method and time discretization is performed using the backward first-order difference method, resulting in the mass conservation discrete control equation with pressure as the solution parameter, i.e., the pressure discrete equation, as shown in equation (12):

[0081] (12)

[0082] in, i and j Indicates the index of the grid nodes that have a link relationship; For the firsti The first grid node (well) and the second j The connection conduction coefficient between grid nodes; n Indicates the time step coefficient; z ( i ) indicates the current number i Each grid has a total number of grid link relationships; For the first i The grid node and the first j The density of the aqueous phase fluid between each grid node; For the first n Grid at each moment j Oil phase fluidity; For the first i The grid node and the first j The density of the oil phase (or hydrocarbon phase) fluid between each grid node; For the first n Grid at each moment j The water phase mobility; For the first n +1 moment i The grid node and the first j Hydrocarbon phase pressure coefficient between grid nodes; V This indicates volume, specifically the volume of the mesh. Indicates the first i Reservoir porosity of each grid; For the first i Oil phase fluid density at each grid node; For the first i The density of the aqueous phase fluid at each grid node; Indicates the compressibility coefficient of hydrocarbon phase fluids; Indicates the first n Hydrocarbon phase saturation at a given moment; Indicates the compressibility coefficient of an aqueous fluid; Indicates the first n Water saturation at a given moment; Indicates the overall compression ratio; For the first n +1 moment i Hydrocarbon phase pressure of each grid; g Represents gravitational acceleration; Indicates the first i The grid node and the first j The depth difference between adjacent grid nodes; , They are grids j Oil phase mobility and water phase mobility; For the first n At the [time]th moment j Oil-water capillary force at each grid node; For the first n At the [time]th moment i Oil-water capillary force at each grid node; For the first n At the [time]th moment i Hydrocarbon phase pressure of each grid; This indicates the time control step size for iterative computation; This indicates the pumping speed of the fluid.

[0083] Spatial discretization is performed using the finite volume method, and time discretization is performed using the backward first-order difference method. The mass conservation discrete control equation with water saturation as the solution parameter is obtained, namely the water saturation discrete equation, as shown in equation (13):

[0084] (13)

[0085] (14)

[0086] in, , They represent the first n +1 moment, the n Each of the following moments i Water saturation of each grid node; Indicates the first i The grid node and the first j Water flow rate between grid nodes; Indicates the first n +1 moment j Water phase pressure at each grid node; Indicates the first n +1 moment i Water phase pressure at each grid node; Indicates total flow; This represents the change in water phase pressure at the i-th network node at time n+1. Indicates the first n +1 moment i The hydrocarbon phase saturation of each grid node. The explanation of the other parameters in equations (13) and (14) can be found in the explanation of the parameters in equation (12), and will not be repeated here.

[0087] After obtaining the pressure discrete equation and the water saturation discrete equation, the pressure discrete equation and the water saturation discrete equation are solved by the matrix preprocessing stable biconjugate gradient iterative solution method, and the pressure distribution field and the water saturation distribution field are obtained. This realizes the numerical calculation of reservoir water saturation and formation pressure distribution during pumping operation, and provides technical support for subsequent hydrocarbon content calculation and further determination of hydrocarbon purity breakthrough time (i.e. hydrocarbon phase breakthrough time). The matrix preprocessing stable biconjugate gradient iterative solution method introduces additional step size parameters and a modified inverse preprocessor to handle the asymmetric matrix linear equation system, which improves the convergence speed and numerical stability. Combined with the stable biconjugate gradient iterative solution method, the pressure field value calculated at each time step is used. Combined with the above equations (13) and (14), the calculation of reservoir water phase and hydrocarbon phase saturation distribution can be further completed, thereby obtaining the pressure distribution field and the water saturation distribution field.

[0088] Step S103: Based on the pressure distribution field, water saturation distribution field, and the characteristics of the spherical flow of the probe node fluid, establish a calculation model for the hydrocarbon content of the probe suction fluid in cable strata testing.

[0089] After obtaining the pressure distribution field and water saturation distribution field, the obtained pressure distribution field and water saturation distribution field can be combined with the spherical flow characteristics of the probe node fluid to establish a calculation model for the hydrocarbon content of the probe suction fluid in cable strata testing. The calculation model for the hydrocarbon content of the probe suction fluid includes: a fluid water content equation, a fluid water flow rate equation, a fluid hydrocarbon flow rate equation, and a fluid hydrocarbon content equation. Specifically, the fluid water content equation is shown in equation (15), the fluid water flow rate equation is shown in equation (16), the fluid hydrocarbon flow rate equation is shown in equation (17), and the fluid hydrocarbon content equation is shown in equation (18).

[0090] (15)

[0091] (16)

[0092] (17)

[0093] (18)

[0094] in, f w Indicates the water content of the fluid at the probe location; Indicates the relative permeability of the oil phase; Indicates the relative permeability of the aqueous phase; Indicates the viscosity of the oil phase fluid; Indicates the viscosity of an aqueous fluid; , and The relationship between the water saturation distribution field and equation (13) is shown in equations (6), (7), and (8); q w Indicates the fluid flow rate at the probe; Q Indicates the pumping speed of the fluid; q o Indicates the hydrocarbon flow rate at the probe; f o This indicates the hydrocarbon content of the fluid at the probe location.

[0095] The obtained probe suction fluid hydrocarbon content calculation model is essentially a function equation about time. Based on this model, a curve showing the relationship between hydrocarbon content (i.e., hydrocarbon purity) and pumping time can be plotted; this curve can be called the hydrocarbon content curve. Based on the hydrocarbon content curve, the hydrocarbon phase breakthrough time (i.e., the time of the first encounter with hydrocarbons) during probe pumping operations can be determined, providing a basis for identifying oil and gas fluids in different formation types and pumping operation modes. Specifically, the pumping time when the hydrocarbon content first appears greater than 0 and less than 1 on the hydrocarbon content curve is taken as the hydrocarbon encounter time, i.e., the breakthrough time of the hydrocarbon phase at the probe, is called the hydrocarbon phase breakthrough time.

[0096] Step S104: Using the dataset and the probe suction port fluid hydrocarbon content calculation model, simulate and calculate the hydrocarbon content curves of the same type of formation oil and gas classification, and construct a clustering map for oil and gas reservoir fluid property identification.

[0097] Specifically, the system utilizes datasets and a probe suction port fluid hydrocarbon content calculation model to simulate and calculate the hydrocarbon content curve at the suction port of a preset probe size under the same wellbore and pumping operation parameters for the same type of target formation. The corresponding hydrocarbon phase breakthrough time is then determined based on the hydrocarbon content curve. Next, sample data is generated based on the oil and gas type, hydrocarbon content curve, and hydrocarbon phase breakthrough time of the same type of target formation obtained from cable formation testing, constructing a sample set. Then, based on the sample set, a clustering chart is constructed using dynamic time warping and hierarchical clustering algorithms. The clustering chart includes hydrocarbon content curves for oil and gas classification of the same type of formation, as well as the boundaries of these hydrocarbon content curves.

[0098] By simulating the hydrocarbon content curve at a certain probe size inlet under the same wellbore and pumping operation parameters in the same target formation of the same type, the hydrocarbon content curve and hydrocarbon phase breakthrough time of the target formation (or similar formation property data) of the same type of formation tested by the cable formation test are used as sample data. The sample data are used to construct a sample set, which provides a data foundation for the construction of a clustering chart for identifying the fluid properties of the target formation at the bottom of the well in the cable formation test.

[0099] Figure 2The diagram illustrates the hydrocarbon content curves obtained from simulation and monitoring statistical calculations of pumping operations during cable formation testing. Figure 1 ,like Figure 2 As shown, the blue curve represents the hydrocarbon content curve simulated using relevant data from cable stratum testing during pumping operations and a probe suction fluid hydrocarbon content calculation model. The orange data points are obtained through monitoring and statistics during cable stratum testing. It is evident that the blue curve and the orange data points have a high degree of fit, indicating that the hydrocarbon content curve obtained through simulation in this application conforms to the actual hydrocarbon content changes over time and has high accuracy. According to... Figure 2 The hydrocarbon phase breakthrough time was determined to be 200s. Given that the reservoir's oil and gas phase fluids are known to be oil-phase (i.e., the oil and gas type is oil-phase), data from the cable formation test, including the target formation, wellbore, pumping, and fluid properties, along with the simulated hydrocarbon content curve, hydrocarbon phase breakthrough time, and oil and gas indication information, will be used as sample data for subsequent cluster map construction. The oil and gas indication information will be used to identify the oil and gas type.

[0100] After the sample set is constructed, a clustering chart can be built based on the sample set using dynamic time warping and hierarchical clustering algorithms. This provides data support for simulating hydrocarbon content curves during subsequent cable formation testing and pumping operations, as well as for identifying the properties of bottom-hole reservoir fluids based on hydrocarbon phase breakthrough time.

[0101] Hydrocarbon content curves are time series data. To compare the similarity of different hydrocarbon content curves, this application employs Dynamic Time Warping (DTW) to calculate curve similarity. DTW is an algorithm used to measure the similarity between two time series, particularly suitable for handling time series of different lengths, velocities, or phases. The core of DTW is to find an optimal alignment path through dynamic programming that minimizes the "cumulative distance" between the two sequences.

[0102] To highlight the differences in breakthrough time, the curves are not scaled on the X-axis. Instead, curves with the same pumping operation time are extracted from the hydrocarbon content curves of each sample data in the sample set and used as sample curves. This facilitates the calculation of the Euclidean distance between different sample curves using the dynamic time warping algorithm.

[0103] Hierarchical clustering is a classic unsupervised learning algorithm. Its core principle is to construct a hierarchical clustering structure (similar to a tree diagram) by continuously merging or splitting data clusters (or groups), ultimately revealing the inherent hierarchical relationships between data. Unlike algorithms such as K-means, which require pre-specifying the number of clusters, hierarchical clustering does not require pre-defining the number of clusters, and the results have an intuitive hierarchical interpretation. In this embodiment, a bottom-up (agglomerated) approach can be adopted to gradually build the hierarchical structure of clusters. Specifically, starting with each sample data as a separate cluster, the two most similar clusters are continuously merged until all samples are merged into the desired cluster.

[0104] Specifically, a hierarchical clustering algorithm is used to form individual clusters using single sample curves. A dynamic time warping algorithm is used to calculate the distance between each cluster, and a preset number of clusters with distances less than a preset distance threshold are selected for merging. The distance strategy is updated using the merged clusters, and this step is repeated. During the clustering process, pruning operations are performed according to a preset pruning decision until the target clusters for oil and gas classification are obtained. The hydrocarbon content curves corresponding to the target clusters are projected onto a hydrocarbon content curve graph to form a clustering chart. The boundaries of hydrocarbon content curves for the same type of formation oil and gas classification are determined based on the hydrocarbon content curves corresponding to the target clusters and marked on the clustering chart. Those skilled in the art can set the preset distance threshold according to actual needs; no specific limitations are made here.

[0105] For example, using an agglomerative hierarchical clustering algorithm, each sample curve forms a single cluster. A dynamic time warping algorithm calculates the distance between each cluster, and the clusters corresponding to the two closest sample curves are merged. This process is repeated using the nearest neighbor distance update strategy for the merged cluster until a single cluster is formed. Furthermore, during the clustering process, pruning operations are performed according to a preset pruning decision, ultimately forming two target clusters for oil and gas classification. Then, the hydrocarbon content curves corresponding to the target clusters are projected onto a hydrocarbon content curve graph, thus forming a clustering map for identifying the fluid properties of oil and gas reservoirs.

[0106] Figure 3 A schematic diagram of a clustering chart is shown in Figure 3. The green hydrocarbon content curve represents the gas phase hydrocarbon content curve, the red hydrocarbon content curve represents the oil phase hydrocarbon content curve, and the dashed lines represent the boundaries of the hydrocarbon content curves for the same type of formation hydrocarbon classification. Specifically, the green dashed line is the upper boundary of the gas phase hydrocarbon content curve, and the red dashed line is the lower boundary of the oil phase hydrocarbon content curve. Based on the boundaries of the hydrocarbon content curves for the same type of formation hydrocarbon classification in the clustering chart, the maximum breakthrough time t of the gas phase hydrocarbon content can be extracted. gas_max Minimum breakthrough time t for oil phase hydrocarbon content oil_minThis provides a basis for the subsequent development of identification standards for identifying the fluid properties of oil and gas reservoirs in similar formations using cable strata testing.

[0107] Step S105: Compare the hydrocarbon phase breakthrough time of the actual formation test operation of the same type of formation to be treated with the clustering chart to identify the fluid properties of the formation to be treated.

[0108] Based on the hydrocarbon content curve boundaries of the same type of formation oil and gas classification in the clustering chart, identification criteria for identifying the fluid properties of oil and gas reservoirs can be formulated according to the hydrocarbon phase breakthrough time of actual formation testing operations. This enables the prediction of the oil and gas type of the target formation based on the hydrocarbon phase breakthrough time of the same type of formation, providing a reliable solution for identifying the reservoir fluid properties at the bottom of the well in cable formation testing.

[0109] When it is necessary to identify the fluid properties of the formation to be treated, relevant data from cable formation testing during pumping operations are collected. Combined with a hydrocarbon content calculation model at the probe suction port, a hydrocarbon content curve at the probe point during pumping operations is simulated and calculated to match the actual formation testing results. The hydrocarbon phase breakthrough time is then determined based on the hydrocarbon content curve. Finally, using the established identification criteria, the fluid properties of the formation to be treated can be easily identified.

[0110] Among them, the maximum breakthrough time t of gas phase hydrocarbon content is extracted based on the hydrocarbon content curve boundaries of the same type of formation in the clustering chart. gas_max Minimum breakthrough time t for oil phase hydrocarbon content oil_min When the hydrocarbon phase breakthrough time is less than the maximum breakthrough time t of the gas phase hydrocarbon content. gas_max When the fluid properties of the formation to be treated are determined to be gaseous fluid; when the hydrocarbon phase breakthrough time is greater than the minimum breakthrough time t of the oil phase hydrocarbon content. oil_min When the fluid properties of the formation to be treated are determined to be oil phase fluid; when the hydrocarbon phase breakthrough time is greater than or equal to the maximum breakthrough time t of the gas phase hydrocarbon content. gas_max And less than or equal to the minimum breakthrough time t of oil phase hydrocarbon content oil_min When the hydrocarbon phase breakthrough time is within the interval [t] gas_max , t oil_min If the fluid properties of the formation to be treated are determined to be oil and gas coexisting fluids, i.e., oil and gas mixed phases.

[0111] Figure 4 The diagram illustrates the hydrocarbon content curves obtained from simulation and monitoring statistical calculations of pumping operations during cable formation testing. Figure 2 If the hydrocarbon content curve is a hydrocarbon content curve that is simulated and calculated for the stratum 1 to be treated under cable stratum testing and is consistent with the actual stratum testing operation, then... Figure 4 As shown, based on the hydrocarbon content curve, the hydrocarbon phase breakthrough time is determined to be 600 s. This hydrocarbon phase breakthrough time is less than the maximum breakthrough time t of the gas phase hydrocarbon content.gas_max If so, the fluid properties of the formation to be treated 1 are identified as gaseous fluid.

[0112] Figure 5 The diagram illustrates the hydrocarbon content curves obtained from simulation and monitoring statistical calculations of pumping operations during cable formation testing. Figure 3 If the hydrocarbon content curve is a hydrocarbon content curve that is simulated and calculated for the cable stratum 2 to be treated under cable stratum testing and is consistent with the actual stratum testing operation, then... Figure 5 As shown, based on the hydrocarbon content curve, the hydrocarbon phase breakthrough time is determined to be 13400 s. This hydrocarbon phase breakthrough time is greater than the minimum breakthrough time t of the oil phase hydrocarbon content. oil_min If so, the fluid properties of the formation to be treated, stratum 2, are identified as oil phase fluid.

[0113] According to the wellbore reservoir oil and gas phase fluid property identification method provided in this application, a three-dimensional seepage numerical simulation model and a probe suction port fluid hydrocarbon content calculation model were constructed for cable formation testing. Through dynamic time warping algorithm and hierarchical clustering algorithm, a clustering chart for oil and gas reservoir fluid property identification was constructed, and an identification standard for identifying oil and gas reservoir fluid properties based on the hydrocarbon phase breakthrough time of actual formation testing operations was formulated. By comparing the hydrocarbon phase breakthrough time of actual formation testing operations of the same type of formation to be treated with the clustering chart, the fluid properties of the formation to be treated can be identified conveniently and accurately. This achieves the goal of identifying wellbore reservoir fluid properties based on hydrocarbon phase breakthrough time, providing a reliable solution and technical means for identifying the oil and gas phase fluid properties of underground reservoirs in cable formation testing.

[0114] Figure 6 A structural block diagram of a bottom-hole reservoir oil and gas phase fluid property identification device according to an embodiment of this application is shown, as follows: Figure 6 As shown, the device includes: a data acquisition module 610, a first construction module 620, a second construction module 630, a map construction module 640, and a recognition module 650.

[0115] The data acquisition module 610 is suitable for: acquiring relevant data from cable stratum testing during pumping operations, and forming a dataset.

[0116] The first construction module 620 is suitable for: constructing a three-dimensional seepage numerical simulation model for cable stratum testing, discretizing and solving the mass conservation equation in the three-dimensional seepage numerical simulation model for cable stratum testing, and obtaining the pressure distribution field and water saturation distribution field.

[0117] The second building module 630 is suitable for: establishing a calculation model for the hydrocarbon content of the probe suction fluid in cable strata testing based on the pressure distribution field, water saturation distribution field, and the characteristics of the spherical flow of the probe node fluid.

[0118] The chart construction module 640 is suitable for: using datasets and probe suction port fluid hydrocarbon content calculation models to simulate and calculate hydrocarbon content curves for oil and gas classification of the same type of formation, and constructing cluster charts for oil and gas reservoir fluid property identification.

[0119] The identification module 650 is suitable for: comparing the hydrocarbon phase breakthrough time of actual formation testing operations of the same type of formation to be treated with the clustering chart to identify the fluid properties of the formation to be treated.

[0120] Optionally, the three-dimensional seepage numerical simulation model for cable formation testing is used to simulate the near-wellbore formation reservoir water saturation and formation pressure distribution during the pumping process; the three-dimensional seepage numerical simulation model for cable formation testing includes: model assumptions, mass conservation equation, boundary conditions, initial conditions, and auxiliary equations; the probe suction port fluid hydrocarbon content calculation model includes: fluid water content equation, fluid water flow rate equation, fluid hydrocarbon flow rate equation, and fluid hydrocarbon content equation.

[0121] Optionally, the first building module 620 is further adapted to: discretize the mass conservation equation using the finite volume method to obtain the pressure discrete equation and the water saturation discrete equation; and solve the pressure discrete equation and the water saturation discrete equation using an iterative solution method with matrix preprocessing to stabilize the biconjugate gradient to obtain the pressure distribution field and the water saturation distribution field.

[0122] Optionally, the chart construction module 640 is further adapted to: using a dataset and a probe suction port fluid hydrocarbon content calculation model, to simulate and calculate the hydrocarbon content curve at the preset probe size suction port under the same wellbore and pumping operation parameters of the same type of target formation, and to determine the corresponding hydrocarbon phase breakthrough time based on the hydrocarbon content curve; to form sample data based on the oil and gas type, hydrocarbon content curve and hydrocarbon phase breakthrough time of the same type of target formation tested by cable formation, and to construct a sample set; based on the sample set, to construct a cluster chart through a dynamic time warping algorithm and a hierarchical clustering algorithm; wherein, the cluster chart contains hydrocarbon content curves of the same type of formation oil and gas classification and the boundaries of the hydrocarbon content curves of the same type of formation oil and gas classification.

[0123] Optionally, the chart construction module 640 is further adapted to: extract curves with the same pumping operation time length from the hydrocarbon content curves of each sample data in the sample set as sample curves; form a single cluster using a hierarchical clustering algorithm; calculate the distance of each cluster using a dynamic time warping algorithm, and select a preset number of clusters with close distances for merging; update the distance strategy through the merged clusters, repeat this step, and perform pruning operations according to a preset pruning decision during the clustering process until the target clusters for oil and gas classification are obtained; project the hydrocarbon content curves corresponding to the target clusters onto the hydrocarbon content curve map to form a cluster chart, and determine the hydrocarbon content curve boundaries of the same type of formation oil and gas classification based on the hydrocarbon content curves corresponding to the target clusters, and mark the hydrocarbon content curve boundaries of the same type of formation oil and gas classification in the cluster chart.

[0124] Optionally, the identification module 650 is further adapted to: extract the maximum breakthrough time of gas phase hydrocarbon content and the minimum breakthrough time of oil phase hydrocarbon content based on the hydrocarbon content curve boundaries of the same type of formation in the clustering map; when the hydrocarbon phase breakthrough time is less than the maximum breakthrough time of gas phase hydrocarbon content, determine that the fluid nature of the formation to be treated is gas phase fluid; when the hydrocarbon phase breakthrough time is greater than the minimum breakthrough time of oil phase hydrocarbon content, determine that the fluid nature of the formation to be treated is oil phase fluid; when the hydrocarbon phase breakthrough time is greater than or equal to the maximum breakthrough time of gas phase hydrocarbon content and less than or equal to the minimum breakthrough time of oil phase hydrocarbon content, determine that the fluid nature of the formation to be treated is oil-gas coexistence fluid.

[0125] According to the wellbore reservoir oil and gas phase fluid property identification device provided in this application embodiment, a three-dimensional seepage numerical simulation model and a probe suction port fluid hydrocarbon content calculation model are constructed for cable formation testing. Through dynamic time warping algorithm and hierarchical clustering algorithm, a clustering chart for oil and gas reservoir fluid property identification is constructed, and an identification standard for identifying oil and gas reservoir fluid properties based on the hydrocarbon phase breakthrough time of actual formation testing operations is formulated. By comparing the hydrocarbon phase breakthrough time of actual formation testing operations of the same type of formation to be treated with the clustering chart, the fluid properties of the formation to be treated can be identified conveniently and accurately. This achieves the goal of identifying wellbore reservoir fluid properties based on hydrocarbon phase breakthrough time, providing a reliable solution and technical means for identifying the oil and gas phase fluid properties of underground reservoirs in cable formation testing.

[0126] The present invention also provides a non-volatile computer storage medium storing at least one executable instruction that can execute the well bottom reservoir oil and gas phase fluid property identification method in any of the above method embodiments.

[0127] This invention provides a computer program product, which includes at least one executable instruction or computer program that enables a processor to perform the operation corresponding to the bottom-hole reservoir oil and gas phase fluid property identification method in any of the above method embodiments.

[0128] Figure 7 The diagram shows a structural schematic of a computing device according to one embodiment of the present application. The specific embodiments of the present application do not limit the specific implementation of the computing device.

[0129] like Figure 7 As shown, the computing device may include: a processor 702, a communication interface 704, a memory 706, and a communication bus 708.

[0130] The processor 702, communication interface 704, and memory 706 communicate with each other via communication bus 708. Communication interface 704 is used to communicate with other network elements, such as clients or other servers. Processor 702 executes program 710, specifically performing the relevant steps in the above-described embodiment of the wellbore reservoir oil and gas phase fluid property identification method for computing devices.

[0131] Specifically, program 710 may include program code that includes computer operation instructions.

[0132] The processor 702 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application. The computing device includes one or more processors, which may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0133] Memory 706 is used to store program 710. Memory 706 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0134] Specifically, program 710 can be used to cause processor 702 to execute the bottom-hole reservoir oil and gas phase fluid property identification method in any of the above method embodiments. The specific implementation of each step in program 710 can be found in the corresponding descriptions of the steps and units in the above-described bottom-hole reservoir oil and gas phase fluid property identification embodiments, and will not be repeated here. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the above-described equipment and modules can be referred to the corresponding process descriptions in the foregoing method embodiments, and will not be repeated here.

[0135] The algorithms and displays provided herein are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems can also be used in conjunction with the teachings herein. The required structure for constructing such systems is apparent from the above description. Furthermore, this invention is not directed to any particular programming language. It should be understood that the contents of the invention described herein can be implemented using various programming languages, and the above description of specific languages ​​is for the purpose of disclosing the best mode of implementation of the invention.

[0136] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0137] Similarly, it should be understood that, in order to streamline this disclosure and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof. However, this method of disclosure should not be interpreted as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the claims, inventive aspects lie in fewer than all features of a single foregoing disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of the invention.

[0138] Those skilled in the art will understand that modules in the device of the embodiments can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0139] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features but not others included in other embodiments, combinations of features from different embodiments are intended to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments can be used in any combination.

[0140] The various component embodiments of the present invention can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some or all of the components according to the embodiments of the present invention. The present invention can also be implemented as a device or apparatus program (e.g., a computer program and computer program product) for performing part or all of the methods described herein. Such programs implementing the present invention can be stored on a computer-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0141] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

Claims

1. A method for identifying the phase-state fluid properties of oil and gas in bottom-hole reservoirs, characterized in that, The method includes: Collect relevant data from cable strata testing during pumping operations to form a dataset; A three-dimensional numerical simulation model of seepage in cable strata testing was constructed. The mass conservation equation in the three-dimensional numerical simulation model of seepage in cable strata testing was discretized and solved to obtain the pressure distribution field and the water saturation distribution field. Based on the pressure distribution field, water saturation distribution field, and the characteristics of spherical flow of fluid at the probe node, a calculation model for the hydrocarbon content of the probe suction fluid in cable strata testing is established. Using the dataset and the probe suction port fluid hydrocarbon content calculation model, the hydrocarbon content curves of the same type of formation hydrocarbon classification are simulated and calculated, and a clustering map for hydrocarbon reservoir fluid property identification is constructed. By comparing the hydrocarbon phase breakthrough time of actual formation testing operations of the same type of formation to be treated with the clustering chart, the fluid properties of the formation to be treated can be identified. The step of using the dataset and the probe suction port fluid hydrocarbon content calculation model to simulate and calculate the hydrocarbon content curves for classifying oil and gas in the same type of formation, and constructing a clustering map for identifying oil and gas reservoir fluid properties, further includes: Using the dataset and the probe suction port fluid hydrocarbon content calculation model, the hydrocarbon content curve at the preset probe size suction port is simulated and calculated under the same wellbore and pumping operation parameters in the same type of target formation, and the corresponding hydrocarbon phase breakthrough time is determined based on the hydrocarbon content curve. Based on the oil and gas type of the same type of target formation obtained from cable strata testing, the hydrocarbon content curve, and the hydrocarbon phase breakthrough time, sample data are generated to construct a sample set. Based on the sample set, the clustering map is constructed using a dynamic time warping algorithm and a hierarchical clustering algorithm; wherein, the clustering map includes hydrocarbon content curves of the same type of formation oil and gas classification and the boundaries of the hydrocarbon content curves of the same type of formation oil and gas classification.

2. The method for identifying the phase-fluid properties of oil and gas in bottom-hole reservoirs according to claim 1, characterized in that, The three-dimensional seepage numerical simulation model for cable formation testing is used to simulate the near-wellbore reservoir water saturation and formation pressure distribution during the pumping process. The three-dimensional seepage numerical simulation model for cable stratum testing includes: model assumptions, mass conservation equations, boundary conditions, initial conditions, and auxiliary equations; The calculation model for the hydrocarbon content of the probe inlet fluid includes: fluid water content equation, fluid water flow rate equation, fluid hydrocarbon flow rate equation, and fluid hydrocarbon content equation.

3. The method for identifying the phase-fluid properties of oil and gas in bottom-hole reservoirs according to claim 1, characterized in that, Discretizing and solving the mass conservation equation in the three-dimensional seepage numerical simulation model for cable strata testing to obtain the pressure distribution field and water saturation distribution field further includes: The mass conservation equation was discretized using the finite volume method to obtain the pressure discretization equation and the water saturation discretization equation. The pressure discretization equation and the water saturation discretization equation are solved by an iterative solution method that stabilizes the biconjugate gradient through matrix preprocessing, thereby obtaining the pressure distribution field and the water saturation distribution field.

4. The method for identifying the phase-fluid properties of oil and gas in bottom-hole reservoirs according to claim 1, characterized in that, The construction of the clustering diagram based on the sample set, using dynamic time warping and hierarchical clustering algorithms, further includes: From the hydrocarbon content curves of each sample data in the sample set, the curves with the same pumping operation time are extracted as sample curves; Hierarchical clustering algorithm is used to form a single cluster using individual sample curves; the distance of each cluster is calculated by dynamic time warping algorithm, and a preset number of clusters with a distance less than a preset distance threshold are selected for merging. The distance strategy is updated by the merged clusters, and this step is repeated. During the clustering process, pruning operation is performed according to the preset pruning decision until the target cluster for oil and gas classification is obtained by merging. The hydrocarbon content curves corresponding to the target clusters are projected onto the hydrocarbon content curve graph to form a clustering chart. The hydrocarbon content curve boundaries of the same type of formation oil and gas classification are determined based on the hydrocarbon content curves corresponding to the target clusters, and the hydrocarbon content curve boundaries of the same type of formation oil and gas classification are marked in the clustering chart.

5. The method for identifying the phase-fluid properties of oil and gas in bottom-hole reservoirs according to any one of claims 1-4, characterized in that, The step of comparing the hydrocarbon phase breakthrough time of actual formation testing operations of the same type of formation to be treated with the clustering chart to identify the fluid properties of the formation to be treated further includes: Based on the hydrocarbon content curve boundaries of the same type of formation hydrocarbon classification in the clustering chart, the maximum breakthrough time of gas phase hydrocarbon content and the minimum breakthrough time of oil phase hydrocarbon content are extracted. When the hydrocarbon phase breakthrough time is less than the maximum breakthrough time of the gaseous hydrocarbon content, the fluid properties of the formation to be treated are determined to be gaseous fluid. When the hydrocarbon phase breakthrough time is greater than the minimum breakthrough time of the oil phase hydrocarbon content, the fluid properties of the formation to be treated are determined to be oil phase fluid. When the hydrocarbon phase breakthrough time is greater than or equal to the maximum breakthrough time of the gas phase hydrocarbon content and less than or equal to the minimum breakthrough time of the oil phase hydrocarbon content, the fluid properties of the formation to be treated are determined to be an oil-gas coexisting fluid.

6. A device for identifying the phase-state fluid properties of oil and gas in a bottom-hole reservoir, characterized in that, The device includes: The data acquisition module is suitable for collecting relevant data from cable strata testing during pumping operations to form a dataset. The first construction module is suitable for constructing a three-dimensional seepage numerical simulation model for cable stratum testing, and for discretizing and solving the mass conservation equation in the three-dimensional seepage numerical simulation model for cable stratum testing to obtain the pressure distribution field and the water saturation distribution field. The second construction module is suitable for establishing a calculation model of the hydrocarbon content of the probe suction fluid in cable formation testing based on the pressure distribution field, water saturation distribution field and the spherical flow characteristics of the probe node fluid. The chart construction module is suitable for using the dataset and the probe suction port fluid hydrocarbon content calculation model to simulate and calculate the hydrocarbon content curves of the same type of formation oil and gas classification, and to construct a cluster chart for oil and gas reservoir fluid property identification. The identification module is adapted to compare the hydrocarbon phase breakthrough time of actual formation testing operations of the same type of formation to be treated with the clustering chart to identify the fluid properties of the formation to be treated. The diagram construction module is further adapted to: Using the dataset and the probe suction port fluid hydrocarbon content calculation model, the hydrocarbon content curve at the preset probe size suction port is simulated and calculated under the same wellbore and pumping operation parameters in the same type of target formation, and the corresponding hydrocarbon phase breakthrough time is determined based on the hydrocarbon content curve. Based on the oil and gas type of the same type of target formation obtained from cable strata testing, the hydrocarbon content curve, and the hydrocarbon phase breakthrough time, sample data are generated to construct a sample set. Based on the sample set, the clustering map is constructed using a dynamic time warping algorithm and a hierarchical clustering algorithm; wherein, the clustering map includes hydrocarbon content curves of the same type of formation oil and gas classification and the boundaries of the hydrocarbon content curves of the same type of formation oil and gas classification.

7. A computing device, characterized in that, include: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the bottom-hole reservoir oil and gas phase fluid property identification method as described in any one of claims 1-5.

8. A computer storage medium, characterized in that, The computer storage medium stores at least one executable instruction, which causes the processor to perform the operation corresponding to the well bottom reservoir oil and gas phase fluid property identification method as described in any one of claims 1-5.

9. A computer program product, characterized in that, It includes at least one executable instruction that causes the processor to perform the operation corresponding to the bottom hole reservoir oil and gas phase fluid property identification method as described in any one of claims 1-5.

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