Current Issue https://www.ljgczz.com EN-US https://www.ljgczz.com/EN/current.shtml https://www.ljgczz.com 5 r values锛� of NMR porosity and core lab determining porosity, NMR permeability and core lab determining permeability are 0.99 and 0.86, respectively. For rock cuttings with the same interval and different particle diameters, NMR porosities and core lab determining porosities, NMR permeabilities and core lab determining permeabilities are compared. As the particle diameters of rock cuttings decrease, the correlation coefficients 锛�r values锛� decrease and the correlations become worse. For the particle diameters of rock cuttings are not less than 3 mm, the correlation coefficients 锛�r values锛� between NMR porosities and core lab determining porosities are not less than 0.90, the correlation coefficient 锛�r values 锛� between NMR permeabilities and core lab determining permeabilities are not less than 0.73. The results show that the particle diameters of PDC bit cuttings in mud logging site can also meet the application of NMR logging technology.]]> r² exceeding 0.7. Piecewise function fitting based on ridge regression and nonlinear regression model y=x/锛�b+kx锛� are suitable for non-linear hydrocarbon loss restoration. Compared with the traditional method of hydrocarbon loss restoration, using the quantitative method to restore hydrocarbons in the study area is more scientific and comprehensive, and has a broad prospect of application.]]> 2/C₃銆侊紙C₁+C₂锛�/锛圕₃+C₄+C₅锛夈�丆₂/锛圕₃+C₄锛夈�丆₁/C₃銆侊紙C₁+C₂+C₃锛�/锛圕₄+C₅锛�, a total of 5 parameters are optimized to form a radar chart. The multiparameter gas-oil ratio and density prediction models established from the geometric model have been verified and applied in 14 layers of 5 wells. The average prediction errors for gas-oil ratio and density are 11.55% and 4.71%, indicating that the established models can realize the rapid and accurate classification of hydrocarbon reservoir types,and the application effect is obvious.]]> TOC (Total Organic Carbon) to study the influencing factors and organic matter enrichment patterns of organic matter enrichment. The results show that the main influencing factors of organic matter enrichment are paleosedimentary environment, paleoproductivity, paleotergenous input, etc., and the enrichment of organic matter is positively correlated with phosphorus, zirconium and other elements. It is believed that the basic conditions for the accumulation of organic matter in this area are strong paleoproductivity and rapid sedimentation of terrigenous inputs, and an oxygen-poor reducing environment is formed under the condition of good overlying cover. Based on the logging elements, the machine learning algorithm is used to obtain the organic carbon content while drilling, and the difference in the distribution of organic matter in the trajectory direction of horizontal wells is explored, which provides more abundant materials for deepening the understanding of shale gas accumulation in this area.]]> T₂ cutoff value, there are slight errors in the calculation of important parameters such as movable fluid saturation, irreducible fluid saturation, and pore size distribution, which restrict the further development of NMR logging technology. The NMR spectra are processed by introducing the segmentation technique of NMR spectra (segmented according to transverse relaxation time), the reconstructed signal is obtained and calculated again, and the oil saturation and porosity in the 1-10 ms segment are optimized to establish a two-dimensional interpretation chart. The application of later data has achieved good results, with the interpretation coincidence rate from 75.6% to 81.6%, improving the accuracy of NMR logging interpretation and evaluation, which can meet the needs of rapid identification of fluid properties in the field.]]> 17 and Ph/nC₁₈. Good results have been obtained in water bearing identification of reef limestone reservoirs of 6 development wells in LF X-1 oilfield by using geochemical bright spots and other geochemical logging characteristic parameters, and the coincidence rate of reservoir interpretation is over 90%. The application results show that geochemical logging plays an important role in reservoir evaluation,water bearing identification and geosteering while drilling.]]> 3/t-8.30 m³/t, with an average of 3.60 m³/t, and the total gas content of the coal seam was between 2.78-14.80 cm³/t, with an average of 7.17 cm³/t. Isothermal adsorption experiments shows that the Langmuir volume of the shale is between 3.33-6.49 cm³/g, with an average of 4.78 cm³/g, and the Langmuir volume of the coal seam is between 12.29-21.67 cm³/g, with an average of 17.75 cm³/g. The gas chemical composition is mainly methane. Through methane isotope analysis of coalbed methane, it is shown that the genesis of coalbed methane in this area is complex, including thermal, biogenic, and secondary thermal genesis. It shows that the area has good comprehensive gas-bearing properties in coal bearing strata.]]> 3 Formation in Bohai A Oilfield is braided river delta, well drilling shows that sandstone percent content is between 5%-65%, and in several areas, igneous rocks with thickness of 5.4-22.6 m are distributed as layers in the inner reservoir. Ed₃ Formation can be divided into four lithology-sedimentary facies belt which develop layered igneous rocks, underwater distributary channel, distal-bar sand and sheet sand. Accurate well-seismic calibrating shows that different stratigraphic lithologic structure can be distinguished by seismic amplitude attribute. In the paper, seismic forward models with complicated stratigraphic lithologic structure are designed, to establish mathematical relations of amplitude attribute and sandstone content, result shows that RMS amplitude is 1 160-4 808 and has a three-part relationship with sandstone content when stratigraphic is sand-shale interbedding. RMS amplitude is higher than 7 226 when stratigraphic is sand, shale and igneous rocks interbedding. Sandstone content is in reverse proportion to RMS amplitude. The sandstone content of Ed₃ Formation is described quantitatively in different zones with well drilling correction. The result is applied to fine geologic modelling. 20 development wells have been deployed, the average single well sandstone drilling rate is increased by 22.3% and recovery ratio is increased by 1.2% through model prediction.]]>