Classification and logging identification of reservoir space near the upper Ordovician pinch-out line in Tahe Oilfield

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

Influencing factors of micropores in the graptolite shale of Ordovician Pingliang Formation in Ordos Basin, NW China

Multiple tests were conducted on graptolite shale samples from Middle Ordovician Pingliang Formation in three typical areas in Ordos Basin to investigate the relationship between micro-nano pore structure, graptolite content, rock composition, TOC, maturity, main and trace elements and gas content. The graptolite of Pingliang Formation concentrates in the black shale at the lower section of this layer. Pores in the shale are diverse in types, including pores made by extracellular polymeric substance (EPS), in bio-graptolite body, as inter-granular void of clay minerals, intra-granular, interstitial space between mineral crystals, micro-fractures, and intra-granular dissolution structures etc. Tests show that graptolite affected the sedimentary environment and shale gas accumulation; graptolites content is positively correlated to TOC, in a certain range, specific surface area is positively correlated to TOC and maturity, etc., as overall a lithologic inorganic and organic ratios. The rare earth elements (REE) patterns of the three areas are similar, indicating the same provenance. REE, Fe, Al and Ti content are negatively correlated to TOC, indicating the high REE content is not caused by organic matter enrichment, but related to the absorption of minerals particles. Gas content is positively correlated to specific surface area, TOC and maturity. The above factors contribute to space and size distribution of micro-nano pores in shale. Key words: graptolite shale, pore type, geochemical parameters, Ordovician Pingliang Formation, Ordos Basi

Developmental characteristics of fractures in deep tight sandstone reservoirs in the second Member of the Xujiahe Formation of Zhongjiang Gas Field

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

Logging identification of complex lithology of the Lower Jurassic Da'anzhai Member in the eastern slope of the western Sichuan Depression

In recent years, with the in-depth development of oil and gas exploration in the eastern slope of the western Sichuan Depression, breakthroughs have been made in the research on high-quality gas reservoirs in the Da'anzhai Member of the Ziliujing Formation in this area. Fine logging identification of lithology in the Da'anzhai Member in the eastern slope of the western Sichuan Depression is the core subject of reservoir sweet spot prediction. In this paper, taking the Da'anzhai Member in the western Sichuan Basin as an example, the work flow and comparisons of multi-lithology logging models have been systematically conducted, using a large number of cores, geological data and logging interpretation models. The research shows that there are four main lithologies developed in the Da'anzhai Member, namely shale, marl-bearing limestone, shell limestone and sandstone. Intersection and spider diagram methods can effectively screen out the logging parameters that are sensitive to lithology, including natural gamma (GR), neutron (CNL), deep lateral resistivity (RD), and acoustic wave time difference (AC). The lithology of the Da'anzhai Member in the study area can be identified with high precision via the ''lithology probability factor'', ''BP neural network'' and cluster analysis methods. Among them, the ''lithologic probability factor'' and ''BP neural network'' methods have a prediction accuracy of lithology exceeds 80%. Therefore, these two methods are optimized as the most effective methods for logging identification of lithology in the Da'anzhai Member. This study has certain reference value for the lithology identification of similar gas reservoirs worldwide