水力压裂
油页岩
石油工程
粉碎
断裂(地质)
压裂液
嵌入
井身刺激
地质学
材料科学
导水率
环境科学
制浆造纸工业
岩土工程
矿物学
土壤科学
石油
水库工程
冶金
土壤水分
工程类
古生物学
作者
Mohsen Farrokhrouz,Abbas Taheri,Stefan Iglauer,Alireza Keshavarz
出处
期刊:Fuel
[Elsevier]
日期:2022-12-01
卷期号:329: 125363-125363
被引量:6
标识
DOI:10.1016/j.fuel.2022.125363
摘要
Hydraulic fracturing of tight formations and placing proppants within induced fractures are commonly performed in unconventional shale reservoirs all over the world, especially in North America. However, the overall recovery of these oil and gas resources is very low and hence, production enhancement is inevitable. This study investigated the acidizing of propped fractures as a recovery enhancement method in Eagle Ford shale samples. Experiments were designed using sample slabs having proppants between them. Differing parameters were examined to optimize the fracture conductivity through acidizing. For a range of confining pressures, the fracture conductivity was maximized by minimizing the proppant embedment. A higher acid injection rate was achieved with a 5 % HCl concentration. Proppant concentration and proppant size were found to affect fracture conductivity inversely. However, this trend was not observed to be monotonic. In terms of production parameters, the skin factor determined the optimized conditions at a constant confining pressure. Overall, the optimum conditions for acidizing in the propped fractures were determined while having 5 % HCl concentration, 1 lb/ft2 (4.88 kg/m2) proppant concentration, 600–710 μm of proppant size and 8 ml/min acid injection rate. These findings confirmed the applicability of the method for hydraulic fracturing optimization in Eagle Ford shale samples. It can also be regarded as a primary enhancement method due to its low cost and the process simplicity in comparison to hydraulic fracturing operations. The experimental results of this study would correspondingly enlighten their potential field applications through facilitating appropriate modification with regards to specific operational conditions.
科研通智能强力驱动
Strongly Powered by AbleSci AI