130 results about "Density logging" patented technology

A pore pressure prediction method for fine-grained hybrid sedimentary rock based on variable P-wave velocity includes: carrying out a P-wave velocity test of rock under different effective stresses, determining a function form of the relationship between acoustic velocity and effective stress, fitting the parameters in the function by optimization, and establishing an evaluation model of effective stress influence term by lithology. According to the measured formation pressure data and the effective stress influence term model, the acoustic velocity background value is deduced, the logging curve is preferred, and the acoustic velocity background value logging evaluation model is established. According to the logging curves of DT and DEN, combined with the lithology identification results, the acoustic velocity background value is calculated, and then the effective stress of the formation is obtained, and then the pore pressure is determined according to the overburden pressure.

The invention discloses an underground physical characteristic prediction method and system combining seismic waves and drilling data, and relates to the technical field of geophysical exploration, and the method comprises the steps: collecting original seismic records, carrying out the preprocessing, obtaining a three-dimensional seismic data body, carrying out the complex channel analysis of the three-dimensional seismic data body, extracting the instantaneous amplitude, instantaneous phase and instantaneous frequency attributes, and carrying out the calculation of the instantaneous amplitude, instantaneous phase and instantaneous frequency attributes. Fault features are identified through a coherent body algorithm, an earthquake feature matrix is obtained, depth alignment and correction are carried out on density logging, interval transit time and neutron porosity curves of drill holes, and a standardized drill hole data table is generated; and based on the seismic feature matrix and the standardized drilling data table. According to the method, deep complementation of the earthquake macroscopic information and the borehole local truth value is realized through the geometric perception multi-modal graph neural network and the dynamic gating fusion mechanism, the problems of insufficient cross-modal feature fusion and misalignment of physical rules in the prior art are solved, and the prediction precision and reliability under complex geological conditions are remarkably improved.

The invention relates to the technical field of oil and gas drilling, and discloses a rock density data processing method and system based on machine learning, a terminal and a medium. The photoelectric absorption index, the compensation density and an energy window parameter output through rock density logging are used as input parameters, the photoelectric absorption index and the compensation density of a nominal value are used as labels, a sample library is established, a learning model is established according to the sample library, and an artificial intelligence algorithm is used for processing energy spectrum data measured by the lithologic density logging instrument. The density and photoelectric absorption index evaluation accuracy and the lithologic density logging measurement precision are improved under the condition of complex well holes and stratums, and the exploration requirements of complex reservoirs such as unconventional reservoirs are effectively met.

The invention provides a gas storage single well gas production capacity optimization method, and relates to the technical field of gas storage gas well injection and production, and the method comprises the following steps: building a stable point binomial productivity equation basic theoretical model; establishing a theoretical curve of the gas production capacity and the effective thickness of the stratum by combining the characteristics of short-term strong injection and strong production of the gas storage; establishing an effective thickness productivity evaluation model layout under different production pressure difference conditions; according to sand production test results of different reservoir stratums, combining a density logging curve, and establishing a function relationship between the density and the sand production pressure difference through mathematical fitting; according to the model layout and the function relation between the density and the sand production pressure difference, a reservoir stratum with the appropriate effective thickness and the appropriate sand production pressure difference is selected, and the gas production capacity of a single well is optimized. The density is associated with the sand production pressure difference, a rapid quantitative evaluation technology for the sand production pressure difference of the multi-layer sandstone gas reservoir is established, and the critical sand production pressure difference of different reservoirs can be rapidly calculated.

The invention discloses a method and device for determining the mineral content of a shale oil reservoir. The method comprises the steps that natural gamma-ray spectrum logging data and lithologic density logging data of a target reservoir are obtained; based on the natural gamma-ray spectrum logging data and the lithologic density logging data, obtaining the volume content of a natural gamma-ray response component, natural gamma-ray spectrum logging skeleton data and lithologic density logging skeleton data of the target reservoir; based on the volume content of the natural gamma response component, correcting the lithologic density logging visual skeleton data and the natural gamma-ray spectrum logging visual skeleton data, and based on the corrected lithologic density logging visual skeleton data and the natural gamma-ray spectrum logging visual skeleton data, obtaining the volume content of the unnatural gamma response component of the target reservoir; and obtaining the mineral content of the target reservoir according to the volume content of the non-natural gamma component and the volume content of the natural gamma response component of the target reservoir. The method can be used for universally and effectively evaluating the mineral content of the shale oil reservoir.

The invention relates to the technical field of logging equipment, in particular to a density logging instrument structure and an assembling method.The density logging instrument structure comprises a logging instrument shell, a column body and a gravity center deviation part, the gravity center deviation part enables the gravity center of the shell to deviate to one side of a well wall, a containing cavity is formed in the gravity center deviation part, and a shielding body is arranged in the cavity; the shielding body is provided with a first mounting hole for mounting a radioactive source and a radiation hole, a radioactive source protection piece is arranged in the radiation hole, a gravity center deviation part is provided with a protection cover plate, and a ray window cover plate opposite to the radiation hole is arranged on the protection cover plate; the invention further comprises an assembling method of the structure, such as the steps of fixing the shielding body, plugging the protection piece, installing the radioactive source, installing the protection cover plate and the like. The technical effects that the gravity center of the logging instrument structure deviates to one side of the well wall, the logging instrument can make contact with the well wall surface for measurement conveniently, the assembling method is safe and convenient, and the radioactive source can be effectively protected are achieved.

The invention discloses a shale reservoir capacity analysis method and device, and relates to the technical field of shale gas geological exploration, and the method comprises the steps: obtaining the logging data and ground temperature data of a shale reservoir; the logging data comprises mineral element logging data, density logging data, total organic carbon content and resistivity logging data of each depth point of the shale reservoir; determining the pore volume index of each depth point of the shale reservoir according to the mineral element logging data and the density logging data; the pore volume index reflects an actual pore volume value of the shale reservoir; according to the ground temperature data, the total organic carbon content and the resistivity logging data, the specific surface area index of each depth point of the shale reservoir is determined; the specific surface area index reflects the actual value of the specific surface area of the shale reservoir; and determining a shale reservoir capacity analysis result according to the pore volume index and the specific surface area index. The shale reservoir capacity analysis accuracy can be improved.

The application provides a calculation method of pore pressure of a tectonic compression formation. The calculation method of pore pressure of the tectonic compression formation comprises the following steps: S1, obtaining a density trend curve, and performing integral calculation on the density trend curve to obtain overburden pressure S V ; S2, determining total porosity POR of the formation based on acoustic logging, density logging, neutron logging or nuclear magnetic resonance logging; S3, analyzing characteristics of a target layer section to determine a tectonic compression coefficient ACm_C of the formation; S4, solving a pore pressure coefficient PP of a mudstone section based on a pore pressure model corrected based on the tectonic compression coefficient ACm_C; S5, determining a relationship between effective stress P eff and biot coefficient α and total porosity POR; and S6, inversely deducing a pore pressure coefficient of a reservoir section according to the relationship between the effective stress P eff and the total porosity POR. The application solves the problem of low calculation accuracy of the pore pressure calculation method in the prior art.

The invention discloses a formation pore pressure calculation method, system, equipment and medium, and the method comprises the steps: marking collected lithologic sections and geological stratification, and selecting at least one of collected seismic horizon velocity, density logging, acoustic logging and resistivity logging as sensitive parameters to establish a normal compaction trend line of a middle-shallow normal pressure section; a correction coefficient is adjusted by using the collected pressure measurement data, and finally, a traditional Eaton method formula is improved by using the adjusted correction coefficient, and a new formation pore pressure calculation formula is established; according to the method, the normal compaction trend line is fully utilized, the distortion of the normal compaction stratum is effectively inhibited while the abnormal pressure change is highlighted, the stability is better, the distortion is less, the pressure trend of the overlying stratum does not need to be calculated, parameters are few, the calculation efficiency is high, calculation can be carried out without logging data, the application range is wider, and the method is particularly suitable for low exploration areas without wells and with few wells.

This invention relates to a wave impedance inversion method, comprising the following steps: Step 1, collecting post-stack seismic data, sonic logging curves, density logging curves, lithology-representing curves, and reservoir interpretation results within the work area; Step 2, calculating wave impedance curves based on sonic logging and density logging curves; Step 3, assigning values ​​to various types of reservoirs to obtain formation identification codes; and reconstructing the wave impedance curves using the formation identification codes to obtain reconstructed wave impedance curves; Step 4, performing intersection analysis using the lithology-representing curves and the reconstructed wave impedance curves; Step 5, performing wave impedance inversion on the post-stack seismic data using the reconstructed wave impedance curves. This invention can directly identify effective energy storage with high accuracy.

The invention belongs to the technical field of earthquake comprehensive interpretation research, and discloses a lithofacies identification method based on difference analysis, which comprises the following steps: firstly, calculating to obtain difference data of a longitudinal wave velocity logging curve, difference data of a transverse wave velocity logging curve and difference data of a density logging curve; performing clustering analysis on the difference data of the longitudinal wave velocity logging curve, the difference data of the transverse wave velocity logging curve and the difference data of the density logging curve by using a Gaussian Mixture method according to the drilling lithofacies type to obtain logging lithofacies data; analyzing the lithofacies depth trend of the well logging according to the lithofacies data of the well logging, and predicting the lithofacies space distribution of the well logging by taking the lithofacies depth trend as a constraint and utilizing a Bayesian method; the invention further provides a lithofacies recognition device and equipment based on difference analysis and a storage medium. The lithofacies can be accurately identified, the identification working efficiency is improved, and the method has a good application effect and a good popularization prospect.

The invention belongs to the technical field of oil and gas exploration and development, and relates to a method and system for quantitatively depicting distribution of different types of hydrocarbon source rocks in a few-well area, and the method comprises the steps: obtaining a seismic body, a sedimentary facies diagram, interval transit time logging data and density logging data after target lamination; hydrocarbon source rock seismic reflection characteristics corresponding to different deposits are obtained through a seismic profile map obtained by intercepting a post-stack seismic body; analyzing the types of the hydrocarbon source rocks by utilizing a sedimentary facies diagram, and depicting plane distribution of different types of hydrocarbon source rocks in a target layer according to different types of hydrocarbon source rock development characteristics and sedimentary facies predicted by utilizing the seismic reflection characteristics of the hydrocarbon source rocks; the residual stratum thickness of the target layer is obtained according to the post-stack seismic body, the stratum sand-to-ground ratio of the target layer is predicted, and hydrocarbon source rock thickness distribution in the target layer is depicted according to the residual stratum thickness and the stratum sand-to-ground ratio; and carrying out coupling analysis on the hydrocarbon source rock plane distribution and the hydrocarbon source rock thickness distribution to obtain hydrocarbon source rock space distribution. According to the method, distribution of different types of hydrocarbon source rocks in the less-well area is quantitatively depicted.

The invention relates to a shale reservoir gas saturation measuring method and device, and belongs to the technical field of shale gas exploration, the method comprises the following steps: obtaining a skeleton density curve, a density logging curve and a total organic carbon content curve of a shale reservoir; a target density curve is obtained according to the difference value of the skeleton density curve and the density logging curve; according to a difference value between the target density curve and the total organic carbon content curve, obtaining a gas-containing indication curve; and carrying out normalization processing on the gas-bearing indication curve to obtain a gas saturation curve. According to the gas saturation curve obtained through calculation, the influence of a framework and organic matter is stripped, and the gas saturation can be accurately reflected.

The invention discloses a stratum density calculation method and device for variable energy window gamma density logging and a storage medium. The method comprises the steps that response energy spectrums of a gamma density logging instrument in different known stratum environments are obtained; changing the energy window boundary of the response energy spectrum, and obtaining density counts in different energy window ranges; calculating different density counts to obtain apparent density; performing benchmarking screening based on the apparent density and the stratum true density to obtain an optimal energy window combination; repeating the operation in different known stratum environments to record data, and connecting to obtain a stratum environment-energy spectrum-optimal energy window combined database; acquiring a to-be-detected stratum environment response energy spectrum; screening an existing response energy spectrum with the highest similarity with the response energy spectrum to be detected from the recorded response energy spectrums; and querying an optimal energy window boundary combination of the existing response energy spectrum with the highest similarity in the stratum environment-energy spectrum-optimal energy window combination database, and calculating the optimal energy window boundary combination to obtain a final calculation result. The method can improve the accuracy of stratum density calculation.

The invention discloses a method for predicting shear wave velocity and density logging data of shale formation cycle characteristics, and relates to the technical field of seismic exploration and development. According to the method, input data is divided into a plurality of time sequence fragments, target values are extracted as labels, and the problem of prediction precision reduction caused by a non-unique mapping relation between samples and labels is solved. Through combination of a space-time attention mechanism and a CNN-GRU hybrid model, an STACGN fusion network is constructed, and the capture capability of the model on waveform sample structure features is effectively enhanced. The network can more accurately capture the spatial-temporal characteristics of the input waveform through training and prediction, so that the precision of shear wave speed and density prediction is remarkably improved. Compared with a traditional method, the method has the advantages that the space-time structure characteristics of data can be fully utilized, the prediction result is optimized, and a more accurate measurement basis is provided for shale formation exploration.

The application discloses a method for determining the position of drilling fluid leakage and calculating leakage parameters, which is used for finding the position of well leakage during drilling, calculating the leakage speed and leakage amount of drilling fluid, and estimating the leakage scale. The application describes the principle that the photoelectric absorption cross section Pe value of barite contained in the drilling fluid is abnormally high compared with other rocks, minerals and fluids, and the leakage position is accurately positioned by the characteristics of the high value of the Pe curve measured by the lithology density logging in the leakage well section, and the leakage speed is predicted by the correlation between the Pe logging value and the instantaneous leakage speed, and the leakage amount is calculated by combining the method of multi-mineral analysis with the actual content of barite in the drilling fluid. The method is simple and easy to operate, and the accuracy is reliable. Compared with the data provided by the field, the error of the leakage speed and the leakage amount calculated by the method is small, and the effect is good.

The application discloses a method, device and equipment for identifying sweet spots of shale oil in a salinized lake basin. The method comprises the following steps: firstly, determining a rock structure factor of a stratum based on a natural gamma curve, volume density logging data and skeleton density logging data of the stratum, so as to determine the lithology of the stratum and identify reservoir rock layers in the stratum based on the rock structure factor; then, determining a lamination index of the rock in the stratum based on electrical imaging logging data, so as to identify source rock layers in the stratum based on the lamination index; and finally, identifying a sweet spot development section of the shale oil in the salinized lake basin based on the reservoir rock layers in the stratum and the source rock layers in the stratum. The method can quickly identify the sweet spot development section of the shale oil in the target area, and provides a basis for later oil and gas development.

The application discloses a qualitative identification method for thin-layer mudstone interlayer in volcanic rock, which comprises the following steps: firstly, determining a mudstone section stably existing in the whole area through core observation and logging data, and taking the mudstone section as a standard section; secondly, selecting three curves (a neutron logging curve, an acoustic time difference logging curve and a density logging curve) responding best to the mudstone, standardizing logging curves of the standard section and the volcanic rock section in the whole area, and determining the peak value and the distribution range of the logging curves; selecting sample points with the best effect in the mudstone section and the volcanic rock section, taking the acoustic time difference logging curve as the horizontal coordinate, and taking the neutron logging curve and the density logging curve as the vertical coordinate respectively to establish a logging interpretation chart, qualitatively determining the identification standard of the mudstone and the igneous rock, and predicting the mudstone interlayer in the volcanic rock in a single well according to the chart. The application solves the problem of qualitative identification of the thin-layer mudstone interlayer in the volcanic rock, and provides reliable technical support for the analysis of the remaining oil potential of the igneous rock.

The invention relates to a method for establishing an identification chart of an oil-water dry layer and an interpretation method of the oil-water dry layer, and belongs to the technical field of oil and gas field exploration and development. The method for establishing the identification chart comprises the following steps of: i) acquiring resistivity logging values, interval transit time logging values, density logging values and oil-bearing level values of standard oil layers, standard water layers and standard dry layers of all wells put into production verification in a research area, and respectively calculating K1 values and K2 values of the standard oil layers, the standard water layers and the standard dry layers of all the wells by utilizing a formula I and a formula II; and ii) establishing an oil-water dry layer identification chart based on the K1 and K2 values of the standard oil layer, the standard water layer and the standard dry layer of each well calculated in the step i). According to the method for establishing the identification plate, the difference between the relative values (K1 and K2) of different reconstructed reservoirs is more obvious, so that the oil-water layer identification plate established according to the method is higher in distinction degree and clearer in range boundary.

The invention relates to a shale gas horizontal well fracture pressure prediction method. The method comprises the steps of 1, multi-source data acquisition and intelligent depth correction, wherein logging data, element logging data, logging-while-drilling data, drilling engineering parameters and shaft track data of a target horizontal well section are acquired; 2, multi-scale feature enhancement: generating a high-dimensional feature sequence; step 3, nonlinear feature screening and mixed crustal stress prediction: screening out a key element combination, calculating an initial crustal stress profile through a traditional physical model based on sound wave and density logging data, and training a machine learning residual prediction model by taking the key element combination and other logging features as input to obtain a mixed crustal stress prediction model; adding the initial crustal stress profile and a residual error predicted value by predicting a residual error between a calculated value and an actual measured value of the physical model to obtain final predicted crustal stress data; and 4, calculating and verifying the fracture pressure: deducing the fracture pressure, and verifying a prediction result by using actual fracture test data.

This invention belongs to the field of oil and gas field development technology and discloses a method and equipment for predicting geostress based on the rotation trajectory and measurement data of a wellbore caliper. The method includes: analyzing the rotation trajectory of the wellbore caliper to find elliptical well sections and recording the major and minor axis measurements; calculating the dynamic Young's modulus and dynamic Poisson's ratio, and calculating the static Young's modulus and static Poisson's ratio using empirical formulas for dynamic-static conversion; obtaining the mud pressure based on construction data and calculating the overlying strata pressure through integration of density logging data; calculating the minimum horizontal principal stress based on the pump shutdown pressure; substituting the above parameters into the wellbore stress-strain formula, and obtaining the maximum horizontal principal stress through formula ratio, thus achieving geostress prediction for the target section. This invention can accurately calculate the biaxial stress difference and the maximum horizontal principal stress, effectively reducing the errors caused by wellbore irregularities and wellbore enlargement rate uncertainties in traditional stress relief methods, improving the accuracy of prediction results, and the testing procedure is simple and efficient.

This invention relates to the field of oil and gas field exploration and development, and discloses a logging identification method, system, equipment, and medium for hydrogen-rich reservoirs in clastic rocks. The method includes: identifying oil and gas reservoirs in clastic rock reservoirs based on differences in the conductivity of fluids within the reservoirs; identifying gas reservoirs in clastic rock reservoirs based on differences in the influence of oil and gas on the formation's elastic modulus; and identifying hydrogen-rich reservoirs based on differences in gas density within the gas reservoirs combined with differences in the gas's occurrence environment. The technical solution of this invention comprehensively utilizes logging methods such as shallow and deep resistivity logging, density logging, neutron logging, sonic logging, and natural gamma ray spectroscopy logging to identify hydrogen-rich reservoirs in clastic rock reservoirs, thereby improving the effectiveness and accuracy of hydrogen-rich reservoir identification.

The invention provides a reservoir productivity assessment method and device and related equipment, and the method comprises the steps: obtaining the logging data of a to-be-assessed reservoir target region, and the logging data comprise density logging data and interval transit time logging data; determining a fracturing index according to the logging data; determining a productivity index according to the fracturing index; and evaluating the productivity of the target region of the reservoir to be evaluated according to the productivity index. According to the method and the device, on the basis of a composite index, namely a fracturing index, factors such as inherent attributes of rock mechanics, diagenesis and influence of a crustal stress field on the complexity degree and the transformation volume of a reservoir fracturing fracture network can be comprehensively considered, the reservoir fracturing performance is continuously evaluated, the matching rate of a reservoir fracturing performance evaluation result and an actual condition is increased, and the evaluation accuracy of the reservoir fracturing performance is improved. And the selection precision of the fracturable interval is improved, and the multi-stage fracturing design precision is improved, so that the reservoir productivity evaluation precision is improved.

The application discloses a method for determining biological silicon content in shale gas reservoirs based on lithology density logging data, and solves the problems of complex cost, inability to meet field scale, regional, low-cost evaluation and large calculation error of existing biological silicon content logging calculation methods. The method comprises the following steps: obtaining logging lithology density DEN, logging photoelectric absorption cross-section index Pe and logging natural gamma GR, establishing a ternary calculation equation based on the lithology density logging data, and then calculating the biological silicon content Si_toc in the shale gas reservoirs of the well to be interpreted. The method can be applied in coring wells, and has universal application value for all shale gas wells, and has smaller error and lower cost.

This invention belongs to the technical field of oil well logging equipment and discloses a four-detector lithology density electrode device and detection method, comprising: a housing assembly, inside which are arranged sequentially a first far detector, a first near detector, a source chamber, a second near detector, and a second far detector; the distances of each detector from the source chamber, from largest to smallest, are: second far detector, first far detector, first near detector, and second near detector. This invention uses four detectors, namely the first far detector, the first near detector, the second far detector, and the second near detector. Each detector acquires density logging curves and lithology logging curves by collecting data. Moreover, if any one detector fails, the remaining three detectors can still generate two volumetric density values ​​and at least one formation photoelectric absorption index cross-section value, obtaining the volumetric density and formation photoelectric absorption index cross-section. The entire machine can still guarantee measurement accuracy and perform normal well logging.

The invention relates to the technical field of oil well logging, and provides a magnetophilic density source bin structural design which comprises an instrument shell, a source chamber pin, a magnetophilic cover plate, a fastening screw, a source chamber body, a density source, a source bin screw and a ray window, a T-shaped groove is formed in the magnetophilic cover plate, the source chamber body is arranged in the T-shaped groove, and the density source is arranged in the T-shaped groove. The source chamber main body is fixed on the paramagnetic cover plate through the fastening screw, and the density source is arranged in the source chamber main body; the upper side of the paramagnetic cover plate is rotatably connected with the instrument shell through the source chamber pin, and the lower side of the paramagnetic cover plate is arranged on the instrument shell through the source chamber screw; the ray window is arranged on the instrument shell through a rolling shaft pin, the ray window is located below the source chamber main body, the ray emitting direction of the ray window is tightly attached to the stratum, and the opening direction of the source chamber main body is back to the stratum. The method has the effects of improving the safety of density logging and reducing the well falling probability of the source chamber.

The invention relates to a source bin structure and a density logging instrument, the source bin structure comprises a source bin body, the source bin body is used for being fixedly connected with a logging instrument body, the source bin body is provided with a mounting hole, the axis of the mounting hole is parallel to the axis of the logging instrument body, a source box assembly is slidably connected in the mounting hole, and a radioactive source is mounted in the source box assembly. A ray emitting window is arranged at the position, corresponding to the radioactive source, of the source bin body, and an emitting window plug is fixedly connected to the ray emitting window. The source bin structure can be suitable for a small-diameter logging instrument, and is convenient to install and convenient to popularize and operate on site; the source box disclosed by the embodiment has the advantage of being convenient to take out, so that the radioactive source can be conveniently taken out; according to the embodiment, the ray shielding effect is good, and the center of the radioactive source is close to the ray emergent window.

The invention discloses a spacing determination method, system and device for density logging and a storage medium, and belongs to the technical field of pulse radioactive source logging in oil-gas exploration. Comprising the following steps: establishing a stratum detection model by utilizing Monte Carlo simulation software; obtaining the relationship between the counting rate and the long source spacing and the relationship between the counting rate and the short source spacing through a stratum detection model, and preliminarily screening the value ranges of the long source spacing and the short source spacing; further screening the value ranges of the long spacing and the short spacing according to the statistical error and the measurement precision of the stratum detection model; and determining a final value range of the short spacing by using a short spacing compensation function and a sensitivity requirement. The method can quickly determine the value range of long spacing and short spacing, has higher accuracy, is reasonable, can help to improve the accuracy of density instrument data, obtains high-precision stratum density parameters, enables subsequent logging interpretation and analysis to be more accurate, and improves the accuracy of the density instrument data. And certain logging cost can be saved.

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 petroleum well logging, in particular to a post-casing density logger calibration method and device, and the method comprises the steps: DOE test design: preparing A types of casing simulation parts with different thicknesses, N types of cement sheath simulation parts with different density values, cement sheath simulation parts with different thicknesses and B types of standard density modules with different densities, and adopting a multi-factor orthogonal test method to obtain a standard density module with different densities; performing full combination test on each sleeve simulation piece, each cement sheath simulation piece, each cement sheath simulation piece and each standard density module; data acquisition: sequentially installing post-sleeving density logging instruments in different combinations of simulation devices, and generating a group of data in each test scene; and correction: establishing a multivariable correction model between the measured data of the post-casing density logging instrument and the standard density module, and eliminating attenuation interference of the casing and the cement sheath. By introducing the multi-dimensional parameter combination of the thickness of the casing, the density of the cement sheath and the thickness, the influence of the underground casing and the cement sheath on the measurement of the stratum density is basically eliminated.