在地质建模和井眼测井提取的辅助下,基于矢量的三维井眼轨迹优化

IF 2.6 Q3 ENERGY & FUELS Upstream Oil and Gas Technology Pub Date : 2021-09-01 DOI:10.1016/j.upstre.2021.100053
Mohammed K. Almedallah , Abdulrahman A. Al Mudhafar , Stuart Clark , Stuart D.C. Walsh
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引用次数: 4

摘要

本文介绍了一种新的策略,利用基于矢量的方法优化三维(3D)定向井眼轨迹的钻井时间,该方法受钻井和地质条件的限制。许多现有的井眼轨迹模型都需要人工输入某些地质约束条件,如地层倾角或开井极限。相比之下,这种基于向量的方法通过建立地质模型,并提取沿井径关键点的井眼测井,确保自动满足地质约束。该方法采用线性逼近约束优化(COBYLA)和遗传算法(GA)全局优化的确定性优化技术,并将其进行比较,以确定最佳的3D井眼轨迹。在优化路径时,该模型根据预先确定的狗狗曲线严重程度、倾角和方位角,根据地下地层强度和深度确定最佳启动点。该方法适用于无约束和有约束地质环境中具有不同数量堆积和下降段的井眼轨迹。结果表明,在不使用地质建模的情况下,COBYLA和遗传算法具有可比性,而遗传算法在复杂井道地质辅助优化问题上具有优势。该技术适用于单井轨迹规划,并可在现场开发规划(FDP)期间扩展到优化的一组井。
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Vector-based three-dimensional (3D) well-path optimization assisted by geological modelling and borehole-log extraction

This paper describes a novel strategy to optimize the drilling time of three-dimensional (3D) directional wellbore trajectories using a vector-based approach subject to drilling and geological constraints. Many existing well-path models require manual entry for certain geological constraints such as formation dip or kick-off limit. In contrast, this vector-based approach ensures that geological constraints are automatically satisfied by building a geological model, and extracting a borehole log of key points along the well-path. The presented approach applies and compares a deterministic optimization technique known as Constrained Optimization by Linear Approximation (COBYLA) with a Genetic-Algorithm (GA) global optimization to determine the optimum 3D well path to drill the target. While optimizing the path, the model determines the optimum kick-off point based on the subsurface-formation strength and depth subject to predetermined doglog severity, inclination and azimuth angles. The methodology is applied to well paths with different number of build-up and drop sections in unconstrained and constrained geological settings. Results show that COBYLA and GA are comparable when not using geological modelling while GA is superior for complex well-path geology-assisted optimization problems. The technique is applicable for a single well path planning, and can be expanded to a set of wells being optimized during Field Development Planning (FDP).

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