Operator and Service Provider Collaborate to Successfully Introduce an Automated Advisory System in a Wildcat Exploration Well Offshore Mexico

P. Batruny, M. R. Paimin, M. Allauddin, Felipe Lyra, Linda Doria, B. Castro
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Abstract

Subsurface uncertainty, inadequate offset wells correlation, and high investment cost are some of the biggest drilling challenges in any frontier environment or wild cat exploration wells. These challenges comes with inherent risk on people, environment, assets, and reputation. Mitigating these risks through contingency in the detailed well planning phase as well maximizing operational uptime and efficiency during the well delivery phase, greatly impact the outcome of the well. Digital tools and automation have been a cornerstone in the industry's latest tools to reduce personnel on the rig, as well as minimize downtime and inefficiency. A collaboration of experts between an Operator and Service company was formed during the well planning phase to evaluate the feasibility of an automation platform for a holistic drilling advisory platform that facilitates real time decision making based on downhole and surface data. An offset well study in the area showed that nearby wells experienced recurrence incidents of wellbore instability and downhole pore pressure uncertainty. Modeling iterations for dynamic and static drilling were simulated during pre-planning phase and optimized in real time based on actual downhole and surface data information. Real time models were compared against dynamic models such as Torque and Drag, Hole Cleaning, Pore pressure, ECD (Equivalent Circulating Density), ESD (Equivalent Static Density), and tripping speed (Swab, Surge, etc.). An automated directional drilling tool was run and compared to decisions made by the directional driller to improve the tool's decision-making process for predictive well trajectory parameters. Based on the resultant models, proactive advice was given to the rig in real-time to optimize the input parameters and reduce negative impact to well operation. For example, the practical, real-time visualization helped quickly identify a decreasing pore pressure trend and avoided resultant high overbalance while drilling the 17.5 in. × 22 in. section. The early warning alert allowed swift real time reaction sent to the rig, with mud weight subsequently decreased to 9.2 ppg, avoiding a potential risk of differential sticking stuck pipe incident due to high mud overbalance. Torque and Drag monitoring throughout the well accurately identified few instances of deviation from the trend and models, which detected an early sign of deteriorating wellbore condition which eventually led to a temporary stuck pipe event. Nevertheless, the pipe was freed, which demonstrate that the real time advisory helps in minimizing and avoiding the severe impact of the stuck pipe on the drilling operation. Automated advisory effectively delivered alerts on tight spots while drilling and casing running resulting in a faster 9-5/8 in. liner running in the deviated section. Tripping advisory mode and Real-time modelling of the swab-surge limits successfully allowed the team to avoid critical areas or swabbing events, which increased tripping speed where an opportunity was available and reduced tripping speed when risk of swab/surge was high avoiding well control/well loss events. The automated directional drilling tool increases in accuracy as the dogleg increased. The intelligent advice from the model got closest to the decisions taken by the directional driller, the closer the well got to the planned trajectory. These resulted in improvement and feedback for the pre-planning model such as target radius allowance, formation properties, and optimum drilling parameters. This work takes the first steps towards drilling automation and digital integration of insights and operation. The collaboration between operator and service company resulted in a successful deployment of an automation platform as a solution to manage and mitigate risks as well as optimize drilling operations in exploration wells.
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运营商和服务提供商合作,在墨西哥海上的一口Wildcat勘探井中成功引入了自动咨询系统
地下不确定性、邻井相关性不足、投资成本高是任何前沿环境或野外勘探井的最大挑战。这些挑战伴随着对人员、环境、资产和声誉的固有风险。在详细的井计划阶段,通过应急措施来降低这些风险,并在井交付阶段最大限度地延长正常运行时间和效率,从而极大地影响油井的产出。数字工具和自动化已经成为行业最新工具的基石,以减少钻机上的人员,并最大限度地减少停机时间和低效率。在钻井规划阶段,作业者和服务公司之间形成了专家合作,以评估自动化平台作为整体钻井咨询平台的可行性,该平台有助于根据井下和地面数据进行实时决策。该地区的邻井研究表明,附近的井反复出现井筒不稳定和井下孔隙压力不确定性。在预规划阶段模拟动态和静态钻井的建模迭代,并根据实际的井下和地面数据信息实时优化。将实时模型与动态模型进行比较,如扭矩和阻力、井眼清洗、孔隙压力、ECD(等效循环密度)、ESD(等效静态密度)和起下钻速度(抽汲、浪涌等)。下入了自动定向钻井工具,并与定向钻井人员的决策进行了比较,以改进工具对预测井眼轨迹参数的决策过程。基于所得到的模型,系统实时向钻机提供主动建议,以优化输入参数,减少对井作业的负面影响。例如,实用的实时可视化有助于快速识别孔隙压力下降趋势,并避免在钻进17.5 in时产生高过平衡。× 22英寸部分。早期预警系统可以将实时反应迅速发送到钻井平台,随后泥浆比重降至9.2 ppg,避免了由于泥浆高度过平衡而导致差动卡钻事故的潜在风险。整口井的扭矩和阻力监测准确地发现了一些偏离趋势和模型的情况,发现了井筒状况恶化的早期迹象,最终导致了暂时卡钻事件。尽管如此,钻杆还是被释放了,这表明实时咨询有助于最大限度地减少和避免卡钻对钻井作业的严重影响。在钻井和下套管过程中,自动咨询系统有效地在紧点处发出警报,从而提高了9-5/ 8in的钻进速度。尾管下入斜井段。起下钻咨询模式和抽汲-涌限值的实时建模成功地使团队避免了关键区域或抽汲事件,从而在有机会的情况下提高了起下钻速度,在抽汲/涌风险高的情况下降低了起下钻速度,避免了井控/井漏事件。随着狗腿的增加,自动定向钻井工具的精度也会提高。该模型给出的智能建议越接近定向司的决策,井眼越接近计划轨迹。这些结果对预先规划模型进行了改进和反馈,如目标半径余量、地层性质和最佳钻井参数。这项工作为钻井自动化和洞察与操作的数字化集成迈出了第一步。运营商和服务公司之间的合作成功部署了自动化平台,作为管理和降低风险以及优化探井钻井作业的解决方案。
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