The genesis and prediction of high-porosity and low-permeability sandstone reservoirs are hot spots in oil and gas geology research worldwide. High-porosity and low-permeability sandstone reservoirs are developed in the Cretaceous Bashkirchik Formation of the Luntai Uplift in the northern Tarim Basin, China. In this article, we conducted a systematic study on the geological origin and logging identification of high-porosity and low-permeability tight sandstone based on core observation, thin section, logging index response, and mathematical discrimination methods. The results show that the K1bs sandstone segment in the study area generally contains calcium carbonate, which mainly comes from carbonate rock debris and calcite cement. Calcite cement mainly fills the pores between primary particles, and it is the main factor leading to the densification of the reservoir. The geological origin of the formation of low-permeability layer is mainly due to the early cementation of carbonate, and the development mode of the low-permeability layer is “high content of calcium debris → severe calcium cementation → poor petrophysical properties → formation of low-permeability layer.” The low-permeability layer has the characteristics of high gamma and high resistivity, and the multi-parameter discriminant method established based on the Fisher criterion has a good identification effect for the low-permeability layer. The low-permeability layer has a small thickness, poor stability and continuity, and strong longitudinal heterogeneity, thus it can form a low-permeability baffle inside the reservoir, which greatly reduces the oil and gas migration capacity.

The development characteristics, scale and control factors of fractures are the core subjects of reservoir sweet spot prediction. The sandstone reservoir of the TX2 gas reservoir in the Zhongjiang Gas Field is a typical low porosity and low permeability tight reservoir with strong heterogeneity, but relatively high-quality reservoirs can be found in different well areas and well segments. In this paper, taking the second Member of the Xujiahe Formation (TX2) as an example, the control factors of fractures were systemically investigated via core observation, thin section, logging data, and fracture logging identifications. The results show that shear fractures are mainly developed in the cores, and they generally have high filling rate and poor effectiveness; microfractures can be found based on the vitrinite and cast thin section results. The intersection diagram (semi-quantitative) and the principal component and BP comprehensive identification (quantitative) methods can effectively identify different types of fractures. The combined application of principal component and BP comprehensive identification methods results in an 83.3 % fracture identification probability. Finally, we found that the development of fractures in TX2 is comprehensively affected by lithology, rock thickness, porosity, and faults.

Real drilling near the upper Ordovician pinch-out line in the Tahe Oilfield shows that the drilling encountered karst reservoir. However, due to the transitional position between the denudation area and the overlying area and the special karst geological background, the existing drilling and completion data show that the reservoir space types in this area are complex and diverse. In this article, the classification of reservoir space near the Upper Ordovician pinch-out line and the extraction of logging response characteristics have been carried out based on drilling, logging, core, and crude oil quality data. Through this study, the classification scheme of karst reservoir space in the study area is proposed. The reservoir space types of karst reservoirs include fracture–cave, fracture–pore (light and low resistivity), fracture–pore (heavy and high resistivity), dissolved pore–pore (light and low resistivity), dissolved pore–pore (heavy and high resistivity), isolated pore (relatively isolated distribution of pores and fractures, weakly connected), and cave-type reservoir (sand and gravel filled or semi-unfilled). Furthermore, conventional logging parameters and five parameters sensitive to reservoir properties are extracted. The intersection maps based on the combination forms, fluid properties, and reservoir space effectiveness of different types of reservoir spaces are effective in distinguishing seven types of reservoir spaces and two types of stratified karst reservoirs. In this study, the reservoir space types and logging response characteristics of reservoirs near the Upper Ordovician pinch-out line are defined, which can provide a reliable geological basis for the quantitative identification and distribution evaluation of karst reservoirs.

Tight sandstone gas is an important field for the future development of the oil and gas industry. In the tight gas reservoir of Penglaizhen Formation in Shifang gas field, the water saturation (Sw) of sealed coring cores and the NMR irreducible Sw of conventional cores are measured by using the reservoir physical property tester and NMR analyzer. Combined with the scanning electron microscope results, the reservoir has the characteristics of complex pore structure and high-water saturation. The calculation of Sw by Archie formula, Density log, and φD-φN has a large error. Therefore, how to accurately calculate Sw is an outstanding problem that needs to be resolved. In this paper, we selected AC, EDN, XI, and φe as the parameters for modeling. We have proposed the optimized Gaussian process regression (GPR) method to calculate the Sw of tight sandstone reservoirs. The water saturation curve calculated by the optimized GPR model is in good agreement with the core saturation value. In the error results of well data in the study area, it was found that the relative error and root-mean-square error of the optimized GPR model were the lowest, and it had better calculation accuracy. In addition, in the error results of the nuclear magnetic core samples, it was also found that the optimized GPR model's MMRE was 6.65% and the RMSE was 4.95. In tight sandstone reservoirs with complex pore structure and high-water saturation, the optimized GPR model is helpful to reduce the influence of reservoir shale characteristics, low resistivity characteristics and hidden information of parameter data during the calculation of Sw. It can calculate Sw more efficiently and reflect the characteristics of irreducible Sw more accurately. The optimized GPR model developed for water saturation calculation has broad application prospects.

塔河油田上奥陶统碳酸盐岩储层具有广阔的开发潜力,纵向储集体贯通的井往往能实现高产.上奥陶统碳酸盐岩储层经历多期岩溶、构造等作用而变得十分复杂,储集空间类型多.对于开发而言,亟需寻求创新而有效的识别方法明确研究区储层发育的类型、特征及规模.通过岩心观察,结合常规测井资料,针对划分出的裂缝-孔洞型、裂缝-孔隙型(轻质)、溶孔-孔隙型(轻质)、裂缝-孔隙型(重质)、溶孔-孔隙型(重质)及孤立型孔缝6 种储集空间类型,运用最大似然机器智能学习算法进行测井定量识别,样本的回判率为 93.9%,识别结果与岩心观察结果平均吻合率为 86.1%,表明该方法针对复杂储集空间类型定量识别具有一定的适用性及推广性.

Shell limestone tight reservoirs are developed in the Lower Jurassic Da'anzhai Member of the Sichuan Basin. Fractures are important storage spaces and seepage channels in shell limestone tight oil reservoirs and are key factors for high oil and gas production in wells. In this study, considering the shell limestone reservoir of the Da'anzhai Member on the eastern slope of the Western Sichuan Depression as an example, we used multiple fracture interpretation models based on conventional logging to identify fractures. Our results show that: (1) the reservoirs in the Da'anzhai Member primarily showed low-angle structural fractures, mostly filled with calcite. The effective linear density of fractures in each well varied greatly, which primarily explains the strong heterogeneity of tight reservoirs. (2) The logging response characteristics of the fractured and non-fractured segments differ considerably, and the fractured segment shows the characteristics of high acoustic time difference and low resistivity. (3) The well log recombination method, principal component analysis method, multivariate discriminant method, backpropagation (BP) neural network method, and K-nearest neighbor (KNN) algorithm are used for fracture identification. According to the consistency of the fracture identification results with the core observation results, we established a comprehensive fracture identification standard using the multi-logging method. In this study, we established a fracture identification method based on the coupling of multiple linear and nonlinear multi-logging models through core calibration, which avoids the errors and uncertainties caused by using a single method. Additionally, this study provides a foundation for the control factors and the prediction of fracture distribution.

High variability in diagenetic strength and rock mechanical properties in interbedded sand and shale necessitates a sustained interest in the study of the dynamic and static rock mechanical behavior and failure modes. We have analyzed the rock mechanical behavior, rupture characteristics, and sequences of the clastic reservoirs of the Xu 5 member, Western Sichuan Depression, China. The results indicate that the Xu 5 shale can produce longer plastic creep behavior than tight sandstone at the same load rate. This causes greater stresses to build up inside the shale than in adjacent sandstone formations. The average internal friction angle of sandstone is 43°, whereas the average internal friction angle of shale is 33°. The failure modes of the Xu 5 member sandstone are mainly brittle-tensile failure and brittle X-type shear failure. We observed that the tensile rupture is dominant, accounting for approximately 75.2%. Shale failure forms mainly include plastic-tensile failure and X-type shear failure, in which shear failure accounts for approximately 67.9%. The sequence of failures of similar clastic reservoirs is generally tensile failure or tensile-shear failure to extension failure. We found that the Xu 5 shale has high plasticity, and the stress conditions required for its failure are higher and more complicated. In addition, our test results indicate that, for the same lithology, the tensile failure is the initial rupture rather than shear failure.