Fractured-vuggy reservoirs are a new target in carbonate oil and gas exploration and development. Because of well-developed reservoir bodies, including fractures and caverns, bottom water invasion can be observed in oilfield development, with low utilization efficiency of crude oil in the reservoir. Accordingly, this study focused on the intersection region of the S99 unit of the Tahe fractured-vuggy reservoirs. Based on seismic data, the reservoir bodies can be divided into three types—caverns, fractures, and broken solution pores. Using the same location condition assignment algorithm, four single-type models are fused into a multi-scale discrete three-dimensional geological model of fractured and cavernous reservoirs, and the corresponding fractured-vuggy reservoir model was established for numerical simulation. The single-well historical fitting precision exceeded 85%. Furthermore, the development can be divided into four stages—initial stage of production, peak production stage, liquid control and oil stabilization stage, and scale gas injection stable. Streamlining sweep analysis determined the utilization and distribution characteristics of the remaining oil in the reservoir. It can be concluded that structure, caverns, and fractures were the main controlling factors affecting the remaining oil distribution in the fractured-vuggy reservoir. The fluid exchange among single-well reserve zones was calculated using streamline-based quantitative sweep analysis and interwell flow quantitative analysis method. Through source-sink quantitative analysis, interwell flow relations were derived, and three water breakthrough modes were further concluded: violent flooding, slow ascending of water cut, and low cut or intermittent water production.

The low comprehensive compressibility coefficient characteristic of fracture-vuggy reservoirs often leads to imprecise dynamic reserve calculations. This study introduces a novel method for estimating dynamic reserves, which incorporates a modified comprehensive compressibility coefficient to enhance accuracy. This methodology has been applied to 23 wells in the Tahe Oilfield, resulting in error rates substantially lower than those associated with traditional techniques, thereby markedly enhancing the accuracy of dynamic reserve estimations. Specifically, for karst cave and fracture-vuggy reservoirs, the error rate in dynamic reserve calculations is reduced to under 10%, surpassing conventional methods by more than fivefold. In the case of fractured reservoirs, despite minor fluctuations in error rates due to stress sensitivity, diversion capacity, and channel variations, the proposed method still demonstrates a significant reduction in error rates compared to standard practices.

Identifying and categorizing drilling-induced fractures is pivotal for understanding the mechanisms underlying wellbore instability, drilling fluid loss, and assessing reservoirs using imaging logging data. This study employs a linear elastic stress model around the wellbore, coupled with a tensile failure criterion, to establish a predictive framework for the orientation of drilling-induced fractures. It investigates how engineering parameters like wellbore trajectory and bottomhole pressure influence the distribution of principal stresses around the wellbore, as well as the angle and orientation of drilling-induced fractures relative to the wellbore axis, across various faulting scenarios. The results indicate that drilling-induced fractures exhibit structured arrangements and consistent patterns, often appearing at approximately 180° symmetric intervals and descending in similar orientations. This provides a theoretical basis for their systematic identification and classification. Under different stress conditions, these fractures can manifest as feather-like shapes, “J”-shaped, or transitional states between feather-like and “J”-shaped orientations, as well as “V”-shaped or “M”-shaped orientations. Accurate detection and classification of these fractures are essential for interpreting effective fractures, conducting thorough reservoir evaluations, and predicting appropriate drilling fluid densities to mitigate the wellbore failure risk. Moreover, this knowledge aids in effectively determining the magnitude and direction of in situ stress inversion.