The Permian system in Sichuan Basin is complex in tectono-sedimentary evolution, creating difficulties in restoring the distribution of favorable facies zones and uncertainties in favorable exploration belts. So, through the latest 2D and 3D seismic data as well as drilling and mud-logging data in and around the basin, this evolution was investigated systematically to identify response characteristics and influential factors of major tectonic movements. The relationship of continuous sedimentary evolution was established to every formation and member and the distribution of favorable facies zones with multiple targets was defined to provide an important support for optimizing the favorable exploration belts. After the comprehensive analysis on geological characteristics, it is revealed that (i) multiple factors, including ancient landform before the Permian deposition, and tensile tectonic setting, mantle plume uplift and volcanic eruption in the Permian, affect the tectonic-sedimentary differentiation of the Permian; (ii) representing a regional tensile tectonic setting, the Permian in Sichuan Basin was a sedimentary system of cratonic rifted basin, which controlled the distribution of bioreef-beach facies zones on the margin of multiple strata, laying a foundation for the development of massive lithologic traps; (iii) in the early Triassic, the basin inherited the sedimentary pattern in the late Permian, and exhibited one feature of filling and leveling up due to some effects, for example, ancient land, island chain and underwater uplift at the basin margin. It was a sedimentary system of cratonic depression basin, whose beaches in vertical and lateral accretion might be controlled by microgeomorphology and presented large-scale sheet-like distribution in Qingshuitai area in plane; and (iv) dependent on the analysis of tectono-sedimentary setting and the comprehensive application of 2D and 3D seismic data, the main sedimentary features were defined, such as “one margin and two ribbons” in Qixia Formation, “one uplift and one margin” in Maokou Formation, “three uplifts and three depressions” in Changxing Formation, and “three uplifting forming beaches and three depressions filling and leveling up” in Feixianguan Formation. In addition, the analysis of petroleum geology points that the main exploration domains and prospects of Permian and Triassic in Sichuan Basin will focus on the platform margin zone of Qixia Formation in western basin, the intraplatform highland zone in central-southern basin, the platform margin zone of Maokou Formation in Jian’ge-Nanchong-Shizhu area, the trough in Kaijiang-Liangping area, and the bioreef-beach on the edge of Changxing Formation in shallow shelf of Pengxi-Wusheng-Shizhu area.

There are numerous complex tasks to study gas reservoir engineering. Both research and development (R&D) of artificial intelligence (AI) techniques, that simulate human thinking for diagnosis and analysis, prediction and evaluation, cognition and reasoning, and decision making and optimization, are still in the stage of beginning. And it is urgent to solve some problems of capturing typical application scenarios, definiting human-computer collaboration and division, and optimizing a few tackling directions. Thus, based on theortical researches on gas reservoir engineering and understandings achieved from application practices for a long time, as well as successful probing experiences on intelligent gasfield construction in Sichuan Basin, R&D demands were analyzed and their feasibility was evaluated for new generation of AI techniques used in gas reservoir engineering. In addition, the key points and prospects for technological application were proposed. Results show that (1) gas reservoir engineering studies mainly need AI techniques to improve their efficiency when dealing with complexities, ensure analysis quality with emerged stronger uncertainty, and figure out regularities through human-computer collaboration; (2) for the above requirements, only to systematically implement unique researches on discipline-oriented intelligent transformation can solve deep-seated technical problems; and (3) automatic analysis and prediction, smart clustering and identification, big data-driven knowledge learning and human-computer collaboration to boost intelligence are cores in AI-related researches on gas reservoir engineering. It is concluded that novel human-computer collaboration is the next trend to study gas reservoir engineering. In this paper, both needs and related issues about AI techniques are presented for gas reservoir engineering and the research directions are initially clarified, which may provide reference for future efforts.

Tight oil reservoirs are characterized by complex pore structure, high resistance in fluid flow, and low production, resulting in poor development benefits. Thus, taken the low to ultra-low permeability tight sandstone oil reservoirs of of the Middle Jurassic Shaximiao 1 Member, Gongshanmiao oilfield, central Sichuan Basin, as examples, numerous experimental studies, such as low-velocity fluid flow, constant-rate water flooding and spontaneous imbibition, were conducted on the basis of another one experiment on rock wettability. Experimental results show that (i) generally, the reservoir rocks of Shaximiao 1 Member represent a weak hydrophilic feature. When core samples are fully saturated with formation water, the water phase flow curve assumes a straight line passing through the coordinate origin. There is no start-up pressure or start-up pressure gradient in the formation-water single-phase flow which is consistent with the Darcy's law; (ii) when establishing an irreducible water saturation via oil displacing water, water membrane adsorbed on pore surface may reduce oil-phase flow channels, whereas the Jamin's effect in two-phase flow may increase additional resistance to oil-phase flow. The low-velocity flow curve of oil phase does not pass through the coordinate origin, indicating the existence of start-up pressure or its gradient. The lower the reservoir permeability, the higher the start-up pressure or pressure gradient; (iii) both displacement rate and rock permeability exert great impacts on the performance of water flooding. At a higher rate, not only fingering of injected water in some larger pores but water channeling along fractures are the main controls on the decline of flooding efficiency; (iv) rock permeability may affect imbibition displacement obviously. And for fracture samples, the imbibition displacement efficiency is bigger than that in matrix samples; and (v) after large-scale fracturing in tight oil reservoirs, the induced fractures with high permeability can reduce start-up pressure and its gradient with effect. And as an important means, the single-well huff and puff (water-oil exchange by imbibition) may also ensure these reservoirs in the long-term stable production. The research results are significantly referential for the development of tight reservoirs or shale oil.