A Quantitative Evaluation Method for Lost Circulation Materials in Bridging Plugging Technology for Deep Fractured Reservoirs

Summary Lost circulation is one type of complex engineering problem in the drilling process. Bridging plugging technology is the most common method of lost circulation control in fractured reservoirs by which loss channels are plugged with lost circulation materials (LCMs). A successful application of LCMs requires selecting suitable materials from hundreds of LCM options, preparing the plugging slurry that matches the loss zone conditions, and adopting the appropriate lost circulation control construction technology. Therefore, through this study, we propose a quantitative evaluation method for LCMs to facilitate the selection of suitable LCMs in field applications. First, we propose characteristic parameters of LCMs based on the entire lifecycle of the fracture plugging zone. Subsequently, we design and conduct experiments to evaluate these parameters based on the temperature and pressure characteristics of the loss zone. Then, we calculate the characteristic parameters’ weight coefficients of the LCMs by the fuzzy analytic hierarchy process (FAHP). Finally, we establish a grading index for characteristic parameters and a quantitative scoring model for LCMs, enabling selection based on the quantitative scores. The reliability of the proposed evaluation method is validated through dynamic fracture plugging experiments and field application results. Research results demonstrate that the plugging zone formed by the plugging slurry, composed of high-scoring LCMs, can withstand a maximum plugging pressure exceeding 15 MPa and maintain structural stability at temperatures up to 150°C. The plugging effect of the slurry composed of high-scoring LCMs is significantly superior to that of the slurry composed of low-scoring LCMs. The high-scoring LCMs were successfully applied in a deep well in the Tarim Basin, effectively controlling the lost circulation and protecting the reservoir. This study enriches the evaluation system for LCMs’ characteristic parameters by integrating multiple parameters comprehensively. It transforms the selection process of optimal LCMs from qualitative analysis to quantitative evaluation and optimization, thereby enhancing on-site evaluation and selection processes for LCMs.