Li Wang

In response to the problems of deteriorating quality of newly added reserves of deep and ultra-deep shale oil, significant differences in well efficiency among similar sweet spots, and difficulty in converting resources and production capacity, a deep and ultra-deep shale oil resource conversion evaluation method is proposed based on the entire process of shale oil development. Based on the production dynamics during the initial stage of production, we establish oil well classification standards for deep and ultra-deep shale oil and obtain two types of shale oil development unit classification standards. We construct well efficiency response indicators for development units, well efficiency index and well efficiency index, quantitatively characterizing the comprehensive well efficiency response within the development unit. We construct a production capacity evaluation system for the development of sweet spots that integrates resource utilization, technological economy, and business management. We use the fuzzy comprehensive evaluation method to obtain sweet spot evaluation scores and grades and quantitatively characterize the differences in production capacity construction for the development of sweet spots. On this basis, the “Resource–Productivity Matching Five Step Method” is proposed, which couples the sweet spot evaluation results with the well efficiency index to obtain the final score and evaluation results of resource conversion. The instance application of the M development unit shows that its overall resource conversion efficiency is not high, with only one type of area being a good match and the other areas being basic matches. The evaluation results are relative. This method achieves the integration of “sweet spot advantage (comprehensive score)—well efficiency response (well efficiency index)—conversion effect (final score)” and can identify false matches, improve the objectivity and reliability of evaluation results, and provide a scientific basis and technical support for shale oil block screening, well location deployment, construction planning and other research.

Volcanic rocks are rich in high-quality oil and gas and represent a key future exploration target. However, bottom water coning in complex reservoirs severely reduces extraction efficiency. This study uses numerical simulation to analyze how permeability, oil layer thickness, interlayers, and horizontal well parameters affect water coning. Results indicate that a permeability ratio of 0.02 delays water breakthrough and increases displacement efficiency by 20%. An oil–water volume ratio of 20 improves displacement efficiency and stabilizes water cut rise. Recovery increases by 15% when the oil layer exceeds 25 m in thickness, with coning expanding significantly at 35 m. A 200 m interlayer can reduce water cut rise by 30%. Optimal well spacing of 300–400 m increases recovery by 10–15%, while a horizontal section of 300–500 m improves reserve recovery. Placing the well 35 m from the top of the layer slows water cut rise.

Traditional stress sensitivity experiments are typically conducted under dry conditions, without considering the reservoir’s water content. In reality, the presence of water within pores significantly influences the extent of stress sensitivity damage in tight sandstone oil formations, subsequently affecting the determination of stress sensitivity coefficients during experimentation. By investigating sandstone samples from wells in the Mahu Block of China’s Xinjiang province, we observed that increasing water saturation reduces the stress sensitivity of tight sandstone. By conducting stress sensitivity experiments under varying water content conditions, we found that the stress sensitivity coefficient is not a constant value but decreases as water saturation increases. Based on experimental comparisons, an optimized power-law model for stress-sensitive damage assessment was refined. By conducting stress-sensitive damage assessment experiments under different water content conditions and integrating the concept of comprehensive compression coefficient, an improved stress-sensitive power-law model was established allowing for the influence of water content. The accuracy of this improved model was increased by 46.98% compared to the original power-law model through experimental validation. The research outcomes can enhance the accuracy of permeability and productivity evaluation, providing valuable guidance for unconventional oil and gas development.

The conglomerate matrix and fracture propagation are special in tight conglomerate reservoir with small well spacing. In this article, the fractal propagation characteristics of the fracture network in conglomerate reservoirs are described by experiment and a micro-mathematical model. According to the core slice, the conglomerate reservoir matrix presents the multi-modal pore structure, described as the “pseudo-dual-media” model. Given the above, the unsteady seepage mathematical model, comprehensively considering the fractal fracture network, stress sensitivity of main fractures, and threshold pressure gradient of the reservoir matrix, was developed and analytically solved. The Blasingame type curves for production decline analysis were plotted, and the sensitive parameters were analyzed. The field application was performed for validation. The research results show that the fractal dimension decides the complexity of the fracture network distribution. As it increases, the unsteady flow occurs earlier, and the boundary flow is delayed. The anomalous diffusion exponent represents the smoothness of crude oil migration and a higher value leads to higher resistance to oil migration and larger pressure drawdown for the same production rate. The growth of the threshold pressure gradient within a certain range can result in a localized downward shift of the type curves. The field application in a conglomerate oil reservoir showed that the presented model presents a fitting accuracy 10% higher than that of the conventional SRV model and has high reliability and precision for the production performance evaluation of the small-well-spacing development of tight conglomerate reservoirs.