Simulation-optimization with machine learning for geothermal reservoir recovery: Current status and future prospects

Mohammad Mahdi Rajabi*, Mingjie Chen

*المؤلف المقابل لهذا العمل

نتاج البحث: المساهمة في مجلةShort surveyمراجعة النظراء

3 اقتباسات (Scopus)

ملخص

In geothermal reservoir management, combined simulation-optimization is a practical approach to achieve the optimal well placement and operation that maximizes energy recovery and reservoir longevity. The use of machine learning models is often essential to make simulation-optimization computational feasible. Tools from machine learning can be used to construct data-driven and often physics-free approximations of the numerical model response, with computational times often several orders of magnitude smaller than those required by reservoir numerical models. In this short perspective, we explain the background and current status of machine learning based combined simulation-optimization in geothermal reservoir management, and discuss several key issues that will likely form future directions.

اللغة الأصليةEnglish
الصفحات (من إلى)451-453
عدد الصفحات3
دوريةAdvances in Geo-Energy Research
مستوى الصوت6
رقم الإصدار6
المعرِّفات الرقمية للأشياء
حالة النشرPublished - يوليو 7 2022

ASJC Scopus subject areas

  • ???subjectarea.asjc.2100.2102???
  • ???subjectarea.asjc.1900.1909???
  • ???subjectarea.asjc.2200.2211???

قم بذكر هذا