提高作业效率和成本效益的实用策略:以泰国S1油田水力压裂作业钻机选择策略为例

Thum Sirirattanachatchawan, Sukrit Kanjanarat, Pavin Pirom, Kanwisa Siriphruek, Anan Tantianon, Apiwat Nadoon, Meth Follett, Chatchai Paramart, Arisara Kukiattikoon
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引用次数: 0

摘要

本文旨在通过提供泰国S1油田水力压裂作业钻机选择策略的成功案例,阐述提高作业和成本效率的策略。拟议的综合工作流程涉及所有有关方面,以指定工作范围,分析内部和外部的优缺点,评价可能的情况,并确定采购战略。以非均质砂岩压裂作业的钻机选择为例,在钻井前确定候选钻机的数量是不可能的。因此,压裂钻机选择的典型标准是在选择候选钻机时考虑钻机移动的灵活性。然而,在一个成熟的领域,候选人确认的不确定性是可控的。油藏工程师在3种情况下提供备选方案的数量以进行敏感性分析。SWOT分析和市场调查显示,使用热烟囱钻机代替卡车钻机,可以提高性能和成本。利用每种类型的历史数据进行敏感性分析,表明候选钻机数量和钻机成本对成本节约有显著作用。通过分析和策略,作业性能提高了34%(减少了2个月),节省了100万美元的成本,相当于时间相关成本的24%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pragmatic Strategy for Operational and Cost Efficiency Improvement: A Case Study of Rig Selection Strategy for Hydraulic Fracturing Operation in S1 Oil Field Thailand
This paper aims to elaborate the strategy for operational and cost efficiency improvement by providing an example of a successful case of rig selection strategy for Hydraulic Fracturing Operation in S1 oil field Thailand. The integrated workflow proposed involves all concerned parties to specify the scope of work, analyze internal and external strengths and weaknesses, evaluate possible scenarios, and identify the procurement strategy. As a case of rig selection for fracturing operation in the heterogeneous sandstone, committing the number of candidates before drilling is impossible. Therefore, the typical criteria for fracturing rig selection consider rig move mobility and flexibility in candidate selection. However, in a proven area, the uncertainty of candidate confirmation is manageable. Reservoir engineers provide the number of candidates in 3 scenarios for sensitivity analysis. SWOT analysis and the market survey reveal the possibility to improve both performance and cost by using a warm-stack skidding rig instead of a truck-mounted rig. The sensitivity analysis by using the historical data of each type, indicates that the number of candidates and rig cost play a significant role in cost saving. As a result of analysis and strategy, the operation performance improvesby 34% (2 months reduction) leading to cost-saving by 1MM USD or 24% of the time-dependent cost.
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