Micro-Testing While Drilling for Rate of Penetration Optimization

Magnus Nystad, A. Pavlov
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引用次数: 3

Abstract

The Rate of Penetration (ROP) is one of the key parameters related to the efficiency of the drilling process. Within the confines of operational limits, the drilling parameters affecting the ROP should be optimized to drill more efficiently and safely, to reduce the overall cost of constructing the well. In this study, a data-driven optimization method called Extremum Seeking is employed to automatically find and maintain the optimal Weight on Bit (WOB) which maximizes the ROP. To avoid violation of constraints, the algorithm is adjusted with a combination of a predictive and a reactive approach. This method of constraint handling is demonstrated for a maximal limit imposed on the surface torque, but the method is generic and can be applied on various drilling parameters. The proposed optimization scheme has been tested on a high-fidelity drilling simulator. The simulated scenarios show the method’s ability to steer the system to the optimum and to handle constraints and noisy data.
随钻微测试优化钻速
机械钻速(ROP)是影响钻井效率的关键参数之一。在作业限制范围内,应优化影响机械钻速的钻井参数,以提高钻井效率和安全性,降低建井总成本。在本研究中,采用了一种数据驱动的寻极值优化方法来自动找到并保持最优钻压(WOB),从而使ROP最大化。为了避免违反约束,算法采用了预测和反应相结合的方法进行调整。这种约束处理方法被证明是对地表扭矩施加最大限制,但该方法是通用的,可以应用于各种钻井参数。所提出的优化方案已在高保真钻井模拟器上进行了测试。仿真结果表明,该方法能够将系统引导到最佳状态,并能够处理约束条件和噪声数据。
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