Hongwei Song

Complex carbonate reservoirs feature large-scale karst cavern structures, exhibiting complex pore and bottom water energy distributions, which increase the difficulty of reservoir development and require targeted research. This paper proposes a new method for dynamic reserves calculation in these reservoirs based on the Differential Processing Method (DPM) and aimed at optimizing the development of complex reservoirs. The AD22 unit of the Tarim Oilfield in Xinjiang is taken as the research object, and this reservoir features complex karst and fault characteristics, which traditional reserves calculation methods cannot effectively capture due to its complex heterogeneous distribution. This study constructs a refined reservoir numerical model through 3D geological modeling and impedance inversion techniques, calculates dynamic reserves using the DPM, and compares the result with traditional material balance and production data analysis methods. The results indicate that the DPM has an advantage in estimating the petrophysical parameters and reserve utilization in such reservoirs. The error between the constructed reservoir numerical model and the actual reservoir development historical data is only 2.04%, demonstrating a good reference value. The model shows that more than 60% of the recoverable reserves in the target unit are located in areas shallower than 160 m underground, while the current development degree is only 12.6%. The model shows that the recovery rate is low in the strong bottom water energy areas of the unit, while the recovery potential is high in the weak bottom water areas. Therefore, a differentiated development strategy based on varying bottom water energy is required to enhance development efficiency. The model indicates that this strategy can improve the comprehensive development benefits of the reservoir by 81.66% over the existing baseline, demonstrating significant potential. This study provides new ideas and methods for dynamic reserve estimation and development strategy optimization for complex carbonate reservoirs, verifies the effectiveness of the DPM in evaluating the development of complex bottom water energy reservoirs, and offers data references for related research and field applications.

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.