The unknown nature and complexity of non-uniform formations cause new difficulties and challenges to the accurate detection of electrical instruments in shallow formations. The micro-cylindrically focused logging tool (MCFL) can provide three original measurement curves, RB0, RB1, and RB2, with different detection depths, which reflect the flushing zone resistivity, mudcake resistivity, and mudcake thickness. In this study, the finite element method was used to model and analyze the micro-cylindrically focused logging tool tool in a three-dimensional non-uniform medium model. By converting the partial differential equation into a generalized polar problem, the logging response characteristics of the micro-cylindrically focused logging tool tool at different detection depths and ranges, mudcake thicknesses, flush zones, and mudcake resistivity contrasts were investigated. Inverse processing of the micro-cylindrically focused logging tool data using the least-squares method was used to obtain the flush zone resistivity, mudcake resistivity, and mudcake thickness, based on which the micropotential and microgradient curves were synthesized. In addition, a digital focusing method was proposed to improve the focusing accuracy and flexibility of the instrument, enhancing the performance of the micro-cylindrically focused logging tool. The optimized design of the focusing method significantly improved the detection performance of the pole plate. This plays an important role in the evaluation of thin layers and oil-water reservoirs.

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Due to the unique characteristics of reservoirs in the Yinggehai Basin in the South China Sea, such as high temperature and high pressure (HPHT), low porosity, low permeability, complex pore structure, and high lime content, the log responses of these reservoirs have very complex characteristics, which makes it difficult to evaluate reservoir parameters accurately. In addition, most reservoirs in Ledong Block of the Yinggehai Basin in the South China Sea contain CO 2 , posing great difficulties for subsequent exploration and development. Accurate evaluation of CO 2 layers is of paramount importance for the development of oil and gas fields. In this study, we used a method for the joint inversion of multiple well logs to evaluate the reservoirs and determine CO 2 saturation level and other formation parameters. We optimized the joint inversion model based on the characteristics of the reservoirs in the Yinggehai Basin and adjusted the forward simulation model to consider the effects of high temperature and high pressure on gas density. In view of high lime content in the formations in this area, we adjusted the resistivity forward simulation model to consider the effect of lime content. The inversion results show that the values of porosity, permeability, and water saturation level obtained through inversion are largely consistent with the core data. The CO 2 saturation level determined through joint inversion is 22%, which represents a deviation of less than 10% from the drilling system testing (DST) result, indicating that the joint inversion method is accurate. The error in the water saturation level determined through the joint inversion method is smaller than that in the calculated results from conventional multimineral inversion models. We performed forward simulation of the results calculated with the joint inversion method and compared the results of forward simulation with actual log curves. For the sandstone interval, the results of forward simulation are largely consistent with the actual log curves, indicating that the joint inversion method is accurate. In summary, the method presented in this paper can accurately determine reservoir parameters and provide strong support for the exploration and development of oil and gas fields in the Yinggehai Basin in the South China Sea.

The Yinggehai basin is located in the western part of the South China Sea, the burial depth of the Huangliu and Meishan formations in the target layer is close to 4000 meters, the formation temperature is close to 200 degrees Celsius, and the formation pressure is up to 100 MPa. The reservoir is characterized by low porosity-ultra-low permeability, heavy carbonate cement, complex CO2 content, this leads to complex neutron and density logging effects. The solubility of CO2 Above CH4, the solubility change with temperature and pressure is different from CH4, which makes it difficult to identify the CO2 gas layer. In this paper, based on the difference in the physical characteristics of CO2 and CH4, the Boltzmann equation combined with MCNP software was used to simulate the neutron and density logging responses under different CO2 saturations. Environmental factors such as temperature and pressure, carbonate cement, mud content and pores were studied To measure the effect of logging response, the LM inversion method is used to jointly invert CO2 saturation of density and neutron logs. The purpose of the inversion is to reduce the non-uniqueness of the evaluation of porosity and CO2 saturation. By introducing the Levenberg-Marquardt (LM) method, the neutron logging response equation of the porosity, argillaceous content, CO2, CH4 in the rock and the corresponding temperature and pressure is solved, and also the response equation of above parameters to density logging, where porosity and CO2 content are the key parameters, and the calculation results prove the effectiveness of the method by comparing the sampling data. The results show that the accuracy of the estimated CO2 saturation is increased by 10% compared with the conventional interpretation method, and the new simulation method improves the calculation speed several times compared to the MCNP software. The joint inversion method has been successfully applied to field data, which has greatly improved the saturation evaluation results of traditional logging interpretation methods, can be extended to other fields of nuclear logging simulation and inversion.