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Automated Gas Lift System Optimization Through Combined Data Analyticsand Wellbore Modeling Approach: A Case Study in an Offshore Middle EastOilfield

机译:通过组合数据分析和井筒建模方法自动化气体升力系统优化:以海上肌电田的案例研究

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Systematic and comprehensive analysis of gas lift operations must include historical performance evaluationand heuristic diagnostics for identification of suboptimal performers.Reliable nodal analysis models arenecessary to optimize the gas lift systems.Though some degree of automation is currently possible,this process still takes substantial effort and time.The work presented here is a streamlined,repeatable,and automated workflow to diagnose and optimize gas lift operation through analytics,reliable wellboremodeling and calibration that reduces the time from days to hours.The workflow is also very easilyrepeatable,which makes it very efficient to update when new data is available.The workflow combines the emerging data analytics efforts in the oil and gas industry along withtraditional gas lift optimization guidelines to identify artificial lift-related key recovery obstacles andcorresponding development plans.This novel combined approach proves the effectiveness and necessityof augmented artificial intelligence,and the case study of field analysis and execution further endorse theimpact of such optimization workflow for gas lift assessment and operations.It builds from data-drivenand engineering-based workflows that compute smart metrics and dashboards based on the historical wellproduction and the gas lift systems performance.Several KPIs and metrics are utilized,some of which areindustry standard while others are intuitively built exclusively for this workflow.In this paper,we present the results and challenges in applying this workflow to an offshore Middle Eastoilfield,with over 50 gas lift wells.As always with field data,several aspects of the data had to be addressed.Accuracy and relevancy of data was questionable.We developed several workflows to address the missing/incorrect data to ensure the robustness and credibility of the results from the workflow.Due to the practicalimplication of the analysis,stringent quality control and error margins were maintained throughout theanalysis.No nodal analysis models were available,consequently models were built and calibrated as a partof this effort.Overall field and facility constraints were also incorporated to ensure results were achievablein the field.The optimized operational plan would yield an additional 15 to 20% gains over current production rate.Further benefits by upgrading the gas lift design are also quantified using the proposed workflow.The timerequired to construct,calibrate,and optimize around 50 wells was less than two weeks.
机译:对天然气升力操作的系统和全面分析必须包括历史表现评估和启发式诊断,用于识别次优性表演者。可接受的节点分析模型,以便优化气体升力系统。虽然目前可能的一定程度的自动化,但这种过程仍然需要大量的努力和时间。这里提出的工作是简化,可重复和自动化的工作流程,可通过分析诊断和优化气体升力操作,可靠的井中模糊和校准,从天到几小时减少时间。工作流程也非常轻松,这使得它非常有效当新数据可用时更新。工作流程将新兴数据分析在石油和天然气行业中的努力结合起来,沿着传统的气体提升优化指南,以识别人工升力相关的关键恢复障碍和相应的发展计划。这一新的组合方法证明了8月份的有效性和必要性介绍的人工智能,以及实地分析和执行的案例研究进一步赞同气升评估和操作的这种优化工作流程。基于数据驱动和工程的工作流程,基于历史生产力计算智能度量和仪表板的基于数据驱动和工程的工作流程。燃气升降系统性能。使用KPI和指标,其中一些是IndarDustry标准,而另一些是用于此工作流程的直观。在本文中,我们展示了将此工作流向近海中的结果和挑战,超过50气体升力井。始终具有现场数据,必须解决数据的几个方面。数据的致意和相关性得到了质疑。我们开发了几个工作流来解决丢失/不正确的数据,以确保结果的鲁棒性和可信度Workflow.due到分析的实用性,严格质量控制和错误边距是Makea在整个Theanalysics中.NO Nodal分析模型可用,因此模型被建造和校准,作为这一努力的一部分。还包含了群体和设施限制,以确保结果是该领域的结果。优化的运营计划将额外的15至20次。百分比通过当前的生产速度提升。通过升级气体升力设计,还使用所提出的工作流程来量化燃气升力设计。实时建造,校准和优化50个井的时间不到两周。

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