The Traditional Drilling Optimization Conceptually Deadlocked for Realtime Well Engineering: An Alternate Solution

Abstract

Abstract The industry has seen several methods of drilling optimization over the years. One of optimization's advantages—namely, its innate mathematical rigor—can also be seen as a disadvantage because of the downhole unknown and uncertain conditions. As a result, the traditional mathematical based models suffer from the optimum drilling parameters being inaccurate and more specifically in a non-convergence deadlock in real time and render useless and may lead to infeasibility when used in real time. To address the issue, in this paper, an opto-satisficed time-optimal batch methodology is proposed that brackets the feasible solution space using various engineering models. The analysis results have shown that the convergence optimal bound space was very quick in obtaining an optimal drilling parameter in realtime and the predictability in the test wells has shown the best solution results under uncertainty. It has also been found that the results provide reasonable threshold values when more data is used as the well is drilled. As long as the driller stays within the operational region, the results have shown that the operating parameters are satisfying and good enough for the desirable outcome. In other words, a near-normal engineering solution is achieved. It has been found that the methodology can adapt the operating condition by combining the theoretical engineering models with the realtime measurements. The actual results from drilling several wells are used to illustrate the efficiency of this method over the traditional drilling optimization algorithms. Comprehensive results are presented in the paper with various examples with derived operational parameters when the well is drilled in realtime that satisfy the drilling engineers as well.