Low permeability tight sandstone reservoirs have a high filtrational resistance and a very low fluid flow rate. As a result, the propagation speed of the formation pressure is low and fluid flow behaves as a non-Darcy flow, which typically displays a highly non-linear behavior. In this paper, the characteristics and mechanism of pressure propagation in this kind of reservoir are revealed through a laboratory pressure propagation experiment and through data from an actual tight reservoir development. The main performance mechanism is as follows: A new pressure cage concept is proposed based on the pressure variation characteristics of the laboratory experiments. There are two methods of energy propagation in the actual water injection process: one is that energy is transmitted to the deep reservoir by the fluid flowing through the reservoir, and the other is that energy is transmitted by the elasticity of the reservoir. For one injection well model and one production well model, the pressure distribution curve between the injection and production wells, as calculated by the theoretical method, has three section types, and they show an oblique “S” shape with a straight middle section. However, the actual pressure distribution curve is nonlinear, with an obvious pressure advance at the front. After the injection pressure increases to a certain level, the curve shape is an oblique and reversed “S” shape. Based on the research, this paper explains the deep-seated reasons for the difference in pressure distribution and proposes that it is an effective way to develop low permeability tight reservoirs using the water injection supplement energy method.

The evaluation of flow dynamics in fractured shale oil reservoirs presents significant challenges due to the complex pore configurations and high organic material concentration. Conventional methods for petrophysical and fluid dynamic evaluations are insufficient in addressing these complexities. However, nuclear magnetic resonance (NMR) technology is an effective technique for quantitatively delineating fluid micro-transport properties across the reservoir core. This study presents an experimental methodology rooted in NMR technology to quantify the flow capabilities within the shale oil matrix. This approach incorporates high-pressure saturation flow experiments across seven distinct core samples to gauge the micro-transport phenomena of fluids across various pore dimensions. The results revealed that under high-pressure saturation, shale cores devoid of fractures demonstrated an average crude oil saturation rate of merely 19.44%. Cores with evident stratification exhibited a 16.18% increase in flow capacity compared to their non-stratified counterparts. The flow dynamics within these shale reservoirs exhibited a range of behaviors, from non-linear to linear. In lower-permeability zones, non-linear patterns became increasingly apparent. An NMR T2 spectrum analysis was used to identify the minimum effective pore size conducive to shale oil flow within the matrix, which was between 8 and 10 nanometers. These insights provide a foundation for a deeper understanding of the mechanisms behind oil and gas migration in fractured shale oil matrices, offering valuable insight into their extractive potential.

High saturation pressure reservoirs experience rapid pressure decline during exploitation, leading to significant changes in crude oil phase behavior and a continuous increase in viscosity after degassing, which adversely affects oil recovery. This challenge is particularly acute in tight sandstone reservoirs. To optimize the development strategy for such reservoirs, a series of experiments were conducted using core samples from a high saturation tight sandstone reservoir in the JS oilfield. Gas-dissolved crude oil was prepared by mixing wellhead oil and gas samples, enabling the identification of the critical point where viscosity changes as pressure decreases. Oil-water relative permeability experiments under varying viscosities revealed crude oil mobility trends with declining production pressure. Additionally, physical and numerical simulations of water huff-n-puff processes were performed, while nuclear magnetic resonance methods explored the effects of soaking time on oil-water imbibition. Key findings include the following optimal parameters for water huff-n-puff: (1) initiating the process when formation pressure is 75% of its original level, (2) a soaking time of 48 h, (3) an injection volume of 0.6 pore volumes per cycle, and (4) a 5 MPa pressure reduction per production stage. Numerical simulations further recommend initiating water injection after one year of depletion, with an optimal cumulative injection volume of 18,000 cubic meters, a soaking time of 10 days, and a producing pressure difference of 5 MPa.

One of the important indicators of shale gas reservoir excavation is capacity evaluation, which directly affects whether large-scale shale gas reservoirs can be excavated. Capacity evaluation is the basis of system analysis and dynamic prediction. Therefore, it is particularly important to conduct capacity evaluation studies on shale gas horizontal wells. In order to accurately evaluate the horizontal well productivity of shale gas staged fracturing, this paper uses a new method to evaluate the productivity of Fuling shale gas. The new method is aimed at the dynamic difference of horizontal wells and effectively analyzes the massive data, which are factors affecting the productivity of shale gas horizontal wells. According to the pressure system, production dynamic characteristics, well trajectory position, fracturing transformation mode and penetration depth, 32 wells were divided into four types. Then, based on the classification, the principal component analysis methods can be used to evaluate the horizontal well productivity of shale gas. The new method of capacity evaluation has improved the accuracy by 10.25% compared with the traditional method, which provides a theoretical basis for guiding the efficient development of the horizontal wells of Fuling shale gas.

Shale gas reservoirs typically contain numerous nanoscale pores, with pore size playing a significant role in influencing the gas behavior. To better understand the related mechanisms, this study employs the Gauge-GEMC molecular simulation method to systematically analyze the effects of various pore sizes (5, 10, 20, and 40 nm) on the phase behavior and dew point pressure of the shale gas reservoir components. The simulation results reveal that when pore sizes are smaller than 40 nm, the dew point pressure increases significantly as the pore size decreases. For instance, the dew point pressure in 5 nm pores is 20.3% higher than under macroscopic conditions. Additionally, larger hydrocarbon molecules exhibit a tendency to aggregate in smaller pores, particularly in the 5–10 nm range, where the relative concentration of heavy hydrocarbons (C4+) increases markedly. Moreover, as the pore size becomes larger, the component distribution gradually aligns with experimental results observed under macroscopic conditions. This study demonstrates that pore effects are more pronounced for smaller sizes, directly influencing the aggregation of heavy hydrocarbons and the rise in dew point pressure. These phenomena could significantly impact the diffusivity of shale gas reservoirs and the recovery of condensate gas. The findings provide new theoretical insights into phase behavior changes in nanopores, offering valuable guidance for optimizing shale gas reservoir extraction strategies.

During depressurization-driven shale gas production, methane migration and state transformation in nanopores affect the source composition of produced gas. However, the relative contributions of initially free and initially adsorbed methane remain difficult to quantify at the molecular scale. In this study, we develop a Frame-0-based source-tracing framework for methane recovery in an idealized graphene square nanopore using molecular dynamics simulations under a stepwise depressurization protocol. Radical Voronoi local density and a two-component Gaussian mixture model are used to assign one-time initial labels to methane molecules at Frame 0. PID–preserving cross-frame tracking is then used to quantify the stage-wise and cumulative source contributions from the two initial populations. For the representative case of R = 10 nm and T = 353.15 K, the stage-wise fraction from the initially free population decreases from 79.5% to 62.2% as pressure decreases, while that from the initially adsorbed population increases from 20.5% to 37.8%. Increasing pore width mainly enhances total recovery through the contribution of initially free methane. Increasing temperature improves the contributions from both populations, with a stronger effect on initially free methane. The present results provide a molecular-scale quantitative characterization of methane initial-source attribution under the current stepwise depressurization protocol and establish a source-tracing framework that can be further extended to more realistic pore models.