Two-phase flow behavior in fractured carbonate reservoirs was investigated due to the importance for geothermal and petroleum resource recovery, such as in this study the phase change of volatile oil. This paper presents a semi-analytical method for accurately modeling two-phase flow behavior and quickly predicting the production performance. The fractured carbonate reservoir was modeled with a dual-porosity model, and the phase change and two-phase flow were modeled using the black oil model. The production of the oil phase was obtained through linearizing and solving the mathematical model. The gas phase production was forecast using the producing gas-oil ratio (GOR), calculated using flowing material balance equations. By comparing the semi-analytical solution to the solution of the commercial numerical simulator and applying it to a field case, the accuracy and practicability of the proposed semi-analytical method could be validated. Based on the semi-analytical model, the influences of several critical parameters on production performance were also analyzed. The proposed model was shown to be efficient in evaluating two-phase production performance of horizontal volatile oil wells. Furthermore, the new technique is able to serve as a useful tool for analyzing two-phase production data and making forecasts for volatile oil wells in fractured carbonate reservoirs.

Finding ways to accelerate the effective development of tight sandstone gas reservoirs holds great strategic importance in regard to the improvement of consumption pattern of world energy. The pores and throats of the tight sandstone gas reservoir are small with abundant interstitial materials. Moreover, the mechanism of gas flow is highly complex. This paper is based on the research of a typical tight sandstone gas reservoir in Changqing Oilfield. A strong stress sensitivity in tight sandstone gas reservoir is indicated by the results, and it would be strengthened with the water production; at the same time, a rise to start-up pressure gradient would be given by the water producing process. With the increase in driving pressure gradient, the relative permeability of water also increases gradually, while that of gas decreases instead. Following these results, a model of gas-water two-phase flow has been built, keeping stress sensitivity, start-up pressure gradient, and the change of relative permeability in consideration. It is illustrated by the results of calculations that there is a reduction in the duration of plateau production period and the gas recovery factor during this period if the stress sensitivity and start-up pressure gradient are considered. In contrast to the start-up pressure gradient, stress sensitivity holds a greater influence on gas well productivity.

With the development of the petroleum industry, the importance of low-permeability reservoirs becomes clear. The fracture, which serves as the notable characteristic of a low-permeability reservoir, controls the flow system of reservoir fluid and restrains the development effect. Finding ways to recognize the fracture by using the normal data and building the fracture 3-D model are the important and difficult points of low-permeability development. According to this problem, the authors use a helpful probe. First, from similar outcrop and drilling core study of the fractured original model, the knowledge base of the fracture was built. Second, based on the analysis of the principle of dual-later log identification fracture, the core calibration was used to make logging, and using dual-later log, the fracture in wells was recognized. Third, based on the analysis of the principle of the fractal kriging method, the inter-well fractures were predicted. Finally, the 3-D model of fracture was built with fractural random simulation. The result shows that the 3-D model is in accordance with the fact of the development. So, the method is correct.

This study was conducted to quantitatively evaluate the reservoir damage caused by waterflood-induced velocity sensitivity in the tight oil reservoirs of Block L in the Ordos Basin. This research investigated changes in reservoir pore–throat structure before and after waterflooding through laboratory experiments. A velocity sensitivity characterization model was established as $R_c\left(Q\right)={\displaystyle \frac{\mathrm{Qexp}\left(-\beta {\left[v_{c0}\left(1+\lambda Q^{\eta }\right)\right]}^{\delta }\right)}{2\pi \varphi h{v}_{c0}\left(1+\lambda Q^{\eta }\right)}}$, and the injection volume as Q, and its reliability was validated using both experimental and field data. The results indicate that excessive water injection can lead to permeability damage in the reservoir. Based on this model, the optimal injection rate for Block L was determined to be 16.8 m³/day. Field application of this optimized rate reduced velocity sensitivity-induced particle damage by 21% and improved oil recovery by 1.4%.

The re-evaluation of oil-bearing wells enables finding potential oil-bearing areas and estimating the results of well logging. The re-evaluation of oil bearing is one of the key procedures for guiding the development of lower production wells with long-term production histories. However, there are many limitations to traditional oil-bearing assessment due to low resolution and excessive reliance on geological expert experience, which may lead to inaccurate and uncertain predictions. Based on information gain, three data-driven models were established in this paper to re-evaluate the oil bearing of long-term production wells. The results indicated that the RF model performed best with an accuracy of 95.07%, while the prediction capability of the neural network model was the worst, with only 79.8% accuracy. Moreover, an integrated model was explored to improve model accuracy. Compared with the neural network, support vector machine, and random forest models, the accuracy of the fusion model was improved by 20.9%, 8.5%, and 1.4%, which indicated that the integrated model assisted in enhancing the accuracy of oil-bearing prediction. Combined with the long-term production characteristics of oil wells in the actual oil field, the potential target sweet spot was found, providing theoretical guidance for the effective development of lower production wells in the late period of oilfield development.

This study investigates the impact of stress sensitivity on the L tight sandstone reservoir in the Ordos Basin. Laboratory analyses confirm strong stress-sensitive characteristics. An exponential decline model and optimal drawdown range (6.66–7.69 MPa) were established, with a calculated stress-sensitive radius of 20.21 m. Field application showed a 11.6% reduction in permeability loss rate, 18.2% decrease in stress-induced damage, and 1.16% improvement in oil recovery after drawdown optimization.