19 results about "Cross-plot" patented technology

This invention discloses a method utilizing nuclear magnetic resonance double-T E The method for classifying water flooding levels in well logging is as follows: First, the transverse relaxation rate of nuclear magnetic resonance (NMR), the geometric mean of the mobile fluid portion of the T2 spectrum, and the double T2 spectrum are calculated sequentially using NMR logging data. E The geometric mean difference of the mobile fluid portion of the T2 spectrum was measured. Then, the porosity of different components was obtained by inversion of echo data under long waiting times and short echo intervals. Finally, the percentage content of macroporous components in the total porosity was plotted against the T2 spectrum. E Cross plot of geometric mean difference of the mobile fluid portion of T2 spectrum and plotting of array induced resistivity AT90 and double T E The cross plot of the geometric mean difference of the mobile fluid portion of the T2 spectrum is measured to identify the flooding level of the flooded layer: unflooded layer, low flooded layer, medium flooded layer, and high flooded layer.

The invention belongs to the technical field of oil exploration and development, and discloses a method for identifying volcanic rock weathering crust and interior periods based on multiple seismic attributes, which comprises the following steps: determining a logging chart division boundary; a seismic data volume corresponding to the logging data is read, a cross plot is drawn, and a seismic data volume correction formula is obtained through linear fitting; correcting the seismic data volume of the research area; dividing the corrected data volume through a logging plate division boundary to obtain a first probability volume P1; determining an impedance plate division boundary; performing inversion to obtain an inversion resistance body; dividing the inversion impedance body according to an impedance plate division boundary to obtain a second probability body P2; performing weighted calculation on the P1 and the P2 to obtain a volcanic rock interior period identification parameter body P3; and establishing a recognition plate by using the P3, and determining a division boundary of the recognition plate to obtain a volcanic rock interior period recognition probability body P4. According to the method, well-seismic data unification is realized, and the weathering crust and the inner curtain period can be effectively identified in combination with an impedance inversion data body prediction result.

Provided are a fluid identification method and system, a terminal device, and a machine-readable storage medium, belonging to the field of petroleum exploration. The method comprises: determining a study sample logging curve, a gas logging curve and drilling detection parameters; on the basis of the study sample logging curve, establishing a shallow resistivity and deep resistivity cross plot, and identifying water from among unknown fluids; using the gas logging curve to establish a derived parameter cross plot; using the study sample logging curve and the drilling detection parameters to establish a semi-quantitative evaluation chart of CO2 content based on density porosity and neutron porosity, and a semi-quantitative evaluation chart of CO2 content based on density porosity and porosity difference; on the basis of the derived parameter cross plot, the semi-quantitative evaluation chart of CO2 content based on density porosity and neutron porosity, and the semi-quantitative evaluation chart of CO2 content based on density porosity and porosity difference, identifying CO2, condensate gas and oil in the unknown fluids. By means of the provided method, unknown fluids can be accurately identified, and logging interpretation evaluation accuracy is improved.

The invention belongs to the technical field of formation pore pressure acquisition, and discloses a pore pressure acquisition method and system based on a depth trend line and formation factors, and the method comprises the steps: collecting well leakage, gas cut and overflow in a drilling process, and re-pressing and static pressure data in an oil testing process, and fitting a regression pressure trend line; drawing an engineering pore pressure geological factor interpretation read map, reading interval transit time and density logging values, and calculating formation factors; forming a pressure factor linearly related to the formation pore pressure by combining the regression pressure trend line and the formation factor; and drawing a formation pore pressure-pressure factor cross plot, carrying out linear regression fitting, and calculating the equivalent density of the formation pore pressure. According to the method, various pressure data (such as well leakage, gas cut, overflow and re-pressure and static pressure data in the oil testing process) in the drilling process are collected, the data are used for logarithmic regression fitting, and the obtained pressure trend line can more accurately reflect the change trend of the formation pore pressure along with the depth.

The invention relates to the technical field of oil exploration, and discloses an inter-coal oil-bearing reservoir prediction method and device, a medium and computing equipment. The method comprises the steps that single well curve characteristic analysis is carried out, qualitative analysis is carried out on curves of sound waves, resistivity, porosity and natural potential, and the characteristics of the oil-bearing reservoir are determined; carrying out quantitative analysis on the density and the gamma curve, and carrying out curve fitting; the fitted curve is optimized, and the influence of the coal seam is eliminated; establishing a favorable reservoir indication curve and a sound wave time difference cross plot, carrying out quantitative analysis on the oil-bearing reservoir, and dividing the interval of the oil-bearing reservoir to distinguish the oil-bearing reservoir; well-seismic calibration is carried out, and a coal seam oil-bearing reservoir removal initial model is established based on the favorable reservoir indication curve; and based on the coal seam-removed oil-bearing reservoir initial model, carrying out oil-bearing reservoir prediction, and drawing an oil-bearing reservoir planar graph and an oil-bearing reservoir profile graph. According to the method, the influence of the coal seam is eliminated, the applicability to the oil-containing reservoir between the coal is improved, and the distribution condition of the oil-containing reservoir is conveniently and accurately predicted.

This invention relates to the technical field of reservoir oil-bearing evaluation methods, and discloses a qualitative evaluation method and system for the oil-bearing properties of heterogeneous reservoirs. The qualitative evaluation method for the oil-bearing properties of heterogeneous reservoirs introduces the natural gamma coefficient of variation V. GR This method characterizes the heterogeneity of reservoirs caused by mudstone interlayers. By combining arrayed induced resistivity (RT) and natural gamma (GR) to establish cross plots, the impact of reservoir heterogeneity on oil-bearing evaluation is reduced to some extent, thereby improving the reliability of oil-bearing evaluation for heterogeneous reservoirs. In addition, through actual data statistics and cross plot analysis, combined with well types and sand body structure models, this method establishes an oil-bearing evaluation standard table, making the method highly operable and practical in actual applications. This improves the reliability of oil-bearing evaluation for heterogeneous reservoirs and provides methodological support for reservoir development and reserve upgrading.

The invention relates to the technical field of geophysical well logging interpretation, in particular to a compact sandstone reservoir complex fluid self-adaptive identification method and device, and the method comprises the steps: analyzing the relation between different fluid types and lithology, physical property, pore structure and brittle reservoir characteristic parameters in a histogram and cross plot mode, and qualitatively determining the main control elements of the fluid type difference; constructing required quantization parameters according to the main control elements; performing normalization processing on the logging curve and the quantization parameters; selecting sensitive parameters from the existing logging curve and the constructed quantization parameters by using a spider diagram; fusing the multiple parameters by using a principal component analysis method, and constructing fluid type master control elements; establishing a label database according to the constructed index and the corresponding fluid type; and training and self-adaptive explanation of a complex fluid identification model are carried out. According to the method, the recognition precision of the complex fluid of the compact sandstone reservoir is improved, and a geological foundation is laid for subsequent dessert evaluation and target optimization.

The invention relates to a clastic rock high-quality reservoir identification method based on rotation coordinate transformation. The clastic rock high-quality reservoir identification method comprises the following steps: S1, collecting reservoir characteristic parameters of a clastic rock reservoir and a multi-index data set of a logging curve; s2, according to the multi-index data set, selecting a combination of a plurality of indexes to construct an identification index variable; s3, based on the constructed identification index variables, constructing a core index set by using a main factor analysis method; s4, according to indexes in the core index set, initial rotation coordinates are constructed; s5, based on a rotation coordinate conversion equation, converting the numerical values of the indexes in the original coordinate system into numerical values in a new coordinate system; s6, constructing a secondary cross plot according to the original coordinate system and the new coordinate system; s7, evaluating the secondary cross plot, carrying out discrimination analysis on the discrimination effect, and adjusting the rotation coordinates according to the discrimination analysis result; and S8, according to the finally adjusted secondary cross plot, dividing the reservoir type and the spatial distribution range of the clastic rock reservoir.

The application discloses a stratum boundary identification method and device, electronic equipment and a storage medium. The stratum boundary identification method comprises the following steps: determining a target survey area, obtaining historical logging data corresponding to the target survey area, correcting the historical logging data to obtain corrected logging data, wherein the corrected logging data comprises corrected phosphorus content data; determining a boundary depth range based on the corrected phosphorus content data, and determining a target survey value corresponding to each candidate boundary depth in the boundary depth range; determining a target cross plot based on the target survey value, and determining a target stratum boundary based on the target cross plot. Based on the technical scheme of the embodiment of the application, the stratum boundary identification efficiency can be improved and the stratum boundary identification cost can be reduced on the basis of accurately identifying the stratum interface. Based on the technical scheme of the embodiment of the application, the efficiency and accuracy of the stratum boundary identification are improved, and the cost of the stratum boundary identification is reduced.

The invention belongs to the technical field of rock mass detection, and provides a basement granite distribution range prediction method, system and device and a medium, and the method comprises the steps: obtaining the logging data of a basement layer section of a research area; establishing a lithology identification graph according to the obtained logging data of the substrate layer section of the research area; the lithology identification graph is an MN cross plot, and M is the slope of a straight line on the sound wave and density cross plot; n is the slope of a straight line on the neutron and density cross plot; determining M value and N value ranges of granite; in the MN cross plot, the area belonging to the range of the M value and the N value of the granite is the granite distribution area.

The invention relates to the technical field of oil-gas exploration and development, and particularly discloses a seismic-electric fusion reservoir fluid identification method, which comprises the following steps of: firstly, obtaining a three-dimensional seismic horizon, further obtaining a geological framework of a work area according to the three-dimensional seismic horizon, and inverting electromagnetic data to obtain an inversion resistivity profile; and the inversion resistivity of the target stratum of the work area is obtained by combining the geological framework and the inversion resistivity profile. And based on the resistivity fluid type cross plot, the fluid type of the target layer can be identified by the inversion resistivity of the target layer. Compared with a traditional fluid identification technology, the reservoir fluid identification method integrates the spatial distribution depiction advantage of well-to-seismic combination and the advantage that an electrical method is sensitive to fluid, is not limited to identification of the fluid at the drilling position, can accurately identify the fluid of each reservoir in a work area, and is high in fluid identification accuracy, large in identification range and easy to operate.

The invention discloses a sand-to-ground ratio prediction method and system for constructing a virtual well optimization variation function by using seismic attributes, and the method comprises the steps: determining a lithology division critical value based on the intersection analysis of a gamma curve and a density curve of a real drilling well, carrying out the statistics of the accumulated thickness of sandstone and mudstone of each layer section, and calculating the sand-to-ground ratio data of the real drilling well; extracting seismic attributes from the seismic data of the target area to generate a seismic attribute plane graph; associating well point sand-to-ground ratio data with seismic attribute values to draw a cross plot, constructing a linear regression relational expression, calculating a sand-to-ground ratio determination coefficient of seismic attributes, and screening to obtain sensitive seismic attributes; designing a virtual well network based on the sensitive seismic attributes and assigning the sensitive seismic attributes to form a virtual well data set; on the basis of the virtual well data set, variation function graphs under different well distances are drawn, and optimized variation function parameters are obtained through variation function graph statistics; and based on the optimized variation function parameters, adopting a Gaussian random function algorithm to generate a sand-to-ground ratio plane distribution diagram. Accurate prediction of the sand-to-land ratio of the reservoir is realized.

The invention provides an oil layer dessert identification method and device fusing wavelet time-frequency analysis and deep learning and a medium, and belongs to the field of oil-gas exploration and development. Comprising the following steps that logging data are collected, measurement data of logging curves changing along with the depth and an oil testing and production testing result data set of corresponding layers are established, standardized preprocessing is conducted on original logging data, and a cross plot of different logging curves is drawn; carrying out sensitivity analysis on the logging curve by utilizing the cross plot, carrying out wavelet decomposition after carrying out normalization processing on the sensitive logging curve, and determining an optimal wavelet function and an optimal decomposition scale; a BiLSTM-FCNN oil layer sweet spot recognition model is constructed and trained, sensitive logging curve data is processed by adopting the determined optimal wavelet function and the optimal decomposition scale and then input to the trained model, and an oil layer sweet spot recognition result is output; according to the method, the problem of separation of noise and effective features in original data signals is solved, and the generalization ability of the model under complex geological conditions is improved.

The invention discloses a formation volume density prediction method based on lithology identification, and relates to the technical field of petroleum drilling and completion, and the method comprises the following steps: S1, collecting well logging data of a drilled well in a target work area; s2, obtaining a porosity difference value between the density porosity and the neutron porosity by using the logging data; s3, drawing a cross plot of the logging stratum volume density and the porosity difference value, and identifying the lithology of sandstone and mudstone by using the cross plot; s4, drawing a logarithmic cross plot according to sandstone and mudstone lithology identification results, and fitting on the logarithmic cross plot to obtain a sandstone and mudstone volume density prediction formula logarithmic form; s5, obtaining a sandstone and mudstone volume density prediction formula according to the logarithmic form of the sandstone and mudstone volume density prediction formula; and S6, predicting the sandstone and mudstone volume density of a subsequent new drilled well in the target work area by using a sandstone and mudstone volume density prediction formula. The stratum density prediction precision is improved, and the method has important practical significance on physical property analysis of a subsequent new drilling well stratum in a target work area.

The invention relates to a method for optimizing the reasonable oil pipe size of an injection-production well of a weak water drive sandstone oil and gas reservoir, which comprises the following steps of: 1, determining binomial productivity equation coefficients A and B of a gas well, and establishing a productivity equation; and 2, analyzing and determining the critical sand production pressure difference during gas production of the injection-production well of the target gas storage. And 3, establishing a binomial function relationship between the formation pressure and the accumulative gas production amount. 4, according to the established binomial function relationship, calculating the formation pressure of the target gas storage in the peak peak of peak regulation and gas production in winter; 5, performing dynamic modeling by adopting a node analysis method, and calculating the productivity of different oil pipe sizes under different formation pressures and production pressure differences; and 6, by taking the productivity under the formation pressure in the peak period as a core basis and drawing a cross plot, quantifying and preferably selecting a reasonable oil pipe size according to the conditions that the productivity amplification is 10% and the critical sand production pressure difference is smaller than 3MPa. The blindness of oil pipe type selection is remarkably reduced, and the gas supply capacity and reliability of the gas storage in the peak regulation critical period are ensured.

The invention discloses a data acquisition method, system, equipment and medium for anisotropic strata in an inclined shaft, and relates to the technical field of logging data processing.The method comprises the steps that a continuous oblique angle of any measuring point in the inclined shaft serves as an estimated value of a borehole inclination angle of the measuring point, and the variation range of the borehole inclination angle of the measuring point is set; based on the estimated value of the borehole dip angle of each measuring point, the borehole dip angle change range and the three-dimensional induction logging data, a logging response component combination curve of each measuring point is constructed; performing skin effect correction on the two curves corresponding to each measurement point; and determining the intersection point in the two-dimensional cross plot of the two corrected curves corresponding to each measuring point as the truth value of the borehole dip angle and the truth value of the horizontal conductivity of the corresponding measuring point, and further calculating to obtain the truth value of the vertical conductivity of each measuring point. According to the invention, the truth value of the horizontal conductivity and the truth value of the vertical conductivity of the stratum can be obtained with high precision.

The invention discloses a coal measure strata tight sandstone reservoir identification method and system. The method comprises the following steps: seismic data zero phasing processing; tracking an amplitude zero value reflecting surface corresponding to the coal seam, and extracting wave crest and wave trough amplitude attribute surfaces; calculating an amplitude difference attribute surface; fitting a function relationship by using a scatter cross plot of the amplitude difference attribute value at the well point and the reservoir thickness; threshold value processing is carried out on the amplitude difference attribute surface; the amplitude difference attribute is expanded to the range of the reservoir thickness; constructing equivalent top and bottom reflecting surfaces of the reservoir; filling the amplitude difference attribute value between the equivalent top surface and the equivalent bottom surface of the reservoir to obtain an amplitude difference attribute body; and carrying out tight sandstone reservoir identification by using the amplitude difference attribute surface and the amplitude difference attribute body. According to the method, by calculating the amplitude difference attribute surface and constructing the amplitude difference attribute body, the shielding influence of the seismic strong reflection of the top and bottom surfaces of the coal seam on the sandstone reservoir is counteracted, and the problem that the tight sandstone reservoir of the coal measure strata cannot be accurately identified in the prior art is solved.

The invention discloses a method and system for identifying a basalt construction environment, and the method comprises the steps: calculating a shape coefficient in an REE element composition curve according to the REE abundance of a basalt sample in a to-be-evaluated target region; projecting a first data point formed by a slope coefficient and a curvature coefficient in the shape coefficient into a slope and curvature cross plot, and projecting a second data point formed by an REE logarithmic mean coefficient in the shape coefficient and the magnesium oxide content into a logarithmic mean coefficient and magnesium oxide content cross plot, respectively obtaining projection positions of the two data points; and according to the current projection position, judging the basalt type of the current to-be-evaluated target area. According to the invention, quantitative characterization of construction environment type identification is realized.