Shallow gas, with huge resources, has been confirmed using three dimensional (3D) seismic data and more than 20 drilling sites in the deep water of the LS36 gas field, the Qiongdongnan Basin, the South China Sea. The interface of sedimentary facies in the southern boundary of the basin controls the distribution within the basin of clastic sediments coming from the north and west of the land uplifted. In this study, seismic data and geophysical attributes were used to investigate the controlling effect of the interface of sedimentary facies on the distribution of shallow gas within the basin. Our study shows that the shallow gas is mainly distributed in the Quaternary Ledong Formation in the southwest of the Qiongdongnan Basin, which was observed from acoustic impedance, amplitude versus offset (AVO), and seismic interpretations. The channelized submarine fans that onlap the interface of the sedimentary facies are distributed in a vertically stacked manner and are the main reservoirs for the shallow gas. Therefore, these sedimentary studies show that the sand-rich sediments are distributed along the interface of the sedimentary facies from the southwest to the northeast and are limited to the shallow gas within the basin. The Central Canyon provides an important deep gas source, while the flank of the canyon, gas chimney, and normal faults related to basement uplift provide pathways for vertical and lateral gas migration to form the shallow gas. This study shows that shallow gas may be widely distributed in other marginal sea basins, and sedimentary systems should be further studied in the future.

Recently, drilling wells have encountered rich gas hydrates in fine-grained sediments in the northern South China Sea. Gas hydrate in fine-grained sediments is very heterogeneous, and its physical properties are different from those of oil and gas reservoirs. The reliability of the classical logging saturation evaluation models established for diagenetic reservoirs is questionable. This study used four wells in GMGS3 and GMGS4 to evaluate the effects of the application of three typical methods for evaluating saturation with different principles in the unconsolidated fine-grained sediments: nuclear magnetic logging, sigma logging, and the Archie formula. It was found that the value of the lithologic capture cross-section in sigma logging and the rock’s electrical parameters in the Archie formula affect the accuracy of the model. Therefore, to obtain a reliable saturation value for fine-grained sediments, an innovative method for the calculation of resistivity and acoustic time is proposed to estimate gas hydrate saturation based on logging data, which is most consistent with the results of core analysis. The overall relative error of the verification well was 5.87%, whereas that of the density NMR logging method was 56%, showing that the accuracy of the newly proposed resistivity DT logging method’s saturation formula was significantly improved. Finally, a new model-based cross chart was developed, which can rapidly differentiate gas saturation during drilling.

Although pre-stack inversion has been carried out on reservoir prediction, few studies have focused on the application of pre-stack for seismic inversion in fractured-cavity carbonate reservoirs. In carbonate rock, complicated combinations and fluid predictions in karst caves are remain unclear. Post-stack methods are commonly used to predict the position, size, and fillings of caves, but pre-stack inversion is seldom applied in carbonate karst reservoirs. This paper proposes a pre-stack inversion method for forward modeling data and oil survey seismic data, using both points to indicate the application of pre-stack inversion in karst caves. Considering influence of cave size, depth, and filler on prediction, three sets of models (different caves volume; different fillings velocity of caves; complicated combination of caves) are employed and inverted by pre-stack inversion. We analyze the pre-stack results to depict Ordovician oil bearing and characterize caves. Geological model parameters came from actual data of the Tahe oilfield, and seismic data were synthesized from geological models based on full-wave equation forward simulation. Moreover, a case study of pre-stack inversion from the Tahe area was employed. The study shows that, from both the forward modeling and the oil seismic data points of view, pre-stack inversion is applicable to carbonate karst reservoirs.

The prediction and development of three gases, mainly coalbed methane, shale gas, and tight sandstone gas, in the Huainan coal measures of China, has been the focus of local coal mines. However, due to the overlapping and coexisting characteristics of the three gas reservoirs in Huainan coal measure strata, it is challenging to develop the three gas. The coal mine has been creating a single pool for a long time, resulting in the severe waste of other gas resources in developing the gas-bearing resources in the coal measure strata. The gas-containing reservoir is predicted based on geological, seismic, and logging in Huainan Mining. In addition, determining the excellent area for reference for the development of three gas resources. First, using logging data, mathematical–statistical methods are used to analyze the physical parameters of gas-bearing reservoirs in multi-layered stacked coal seams. Then, based on the theory of prestack seismic inversion, parameters, such as the impedance of P-wave, the ratio of P-wave velocity and S-wave, Lamé constant, Young’s modulus, and Poisson’s ratio and lithological distribution, are obtained for the whole area. The gas-bearing information of the reservoir is received by the statistics and equation of the parameter intersection diagram and is closely related to exploration and development. Finally, the paper synthetically predicts the most favorable area of the gas-bearing reservoir in the study area. The prediction results are compared with the actual results of coalbed methane content in the existing extraction wells, proving that the method is feasible and can provide the basis for the deployment and development of the well location.