基于智能钻井咨询系统的钻井性能优化

M. Abughaban, A. Alshaarawi, Cui Meng, Guodong Ji, Weihong Guo
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引用次数: 4

摘要

钻井过程中钻井参数的优化是获得最大机械钻速(ROP)和最小化钻井成本的关键。计算机技术和通信技术的进步是钻井优化的最重要因素之一。在目前的工作中,开发了一种新的钻机咨询系统,以不断提高ROP和钻井性能。通常,钻井人员根据过去的经验或钻井程序中指定的参数来应用钻井参数(钻头重量、转速和泵速)。这些参数通常在很长一段时间内保持不变,无论钻探的是什么地层。然而,众所周知,保持恒定的钻井参数来驱动钻头会导致多余的切削深度(DOC),诱发粘滑振动,导致低ROP,更高的钻井比能(DSE),并可能损坏底部钻具组合(BHA)。建立了一种基于多元回归分析软闭环解决方案的智能钻井咨询系统(IDAS),称为最优参数全局检索。结合机器学习方法(主成分分析),实时分析钻井参数随岩性变化的响应。此外,通过梯度搜索和决策树算法得到了最优的控制参数方向。该系统实时监测ROP与钻头输入能量之间的关系,并计算出优化的钻井参数。该工作介绍了如何在中国应用IDAS程序,如何解释数据,以及如何获得最佳工作参数,以指导钻井人员提高钻井性能并减少非生产时间(NPT)。IDAS已被引入硬地层钻井,在帮助钻井人员选择合适的工作参数以获得最大ROP方面取得了成功。与常规钻井相比,IDAS导引的现场应用显示出明显的ROP提高。作为进一步实现最佳DOC的有效工具,一种新型控制系统取得了令人满意的结果,克服了沙特阿拉伯和中国的钻井挑战,这将是向自动化钻井作业迈出的一步。
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Optimization of Drilling Performance Based on an Intelligent Drilling Advisory System
Optimization of drilling parameters during drilling operations is a key component to obtain maximum rate of penetration (ROP) as well as minimizing the drilling cost. Advancement in computer technologies and communication are among the most important factors that can contribute to drilling optimization. In the current work, a novel rig advisory system is developed to continually improve ROP and the drilling performance. Conventionally, drillers apply drilling parameters (weight-on-bit, rotary speed and pump rate) according to past experience or to parameters specified in the drilling program. These parameters are usually kept constant over a long interval regardless of the formations being drilled. However, it is well-known that keeping constant drilling parameters to drive the bit will lead to redundant depth of cut (DOC), inducing stick-slip vibration that leads to low ROP, higher drilling specific energy (DSE), and potential damage to the bottom-hole assembly (BHA). An intelligent drilling advisory system (IDAS), based on a soft-closed-loop solution with multiple regression analysis called optimum parameters global retrieval, has been established. Integrated with machine-learning methodology (Principal component analysis), the response of the drilling parameters with lithology changes was analyzed in real time. Additionally, the optimum control parameters direction were obtained from the gradient search and decision tree algorithms. This system monitored the relationship between the ROP and input energy delivered to the bit in real time, and calculated the optimized drilling parameters. The work presented how the IDAS procedures were applied in China, how the data was interpreted, and how optimum working parameters were obtained to guide drillers to improve drilling performance and reduce non-productive time (NPT). IDAS has been introduced to hard formation drilling, which proved to be a success in real-time advisory aiding drillers applying proper working parameters for maximum ROP. Field applications of IDAS guidance showed significant ROP improvement compared to that of conventional drilling. As an effective tool for further achieving the optimum DOC, a novel control system achieved satisfactory outcomes that overcome the drilling challenges in Saudi Arabia and China, which will serve as a step forward towards automated drilling operations.
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