Petroleum Development Oman Forecasting Management System

Hilal Mudhafar Al Riyami, Hilal Mohammed Al Sheibani, Hamed Ali Al Subhi, Hussain Taqi Al Ajmi, Zeinab Youssef Zohny, Azzan Qais Al Kindy
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Abstract

Production performance forecasting is considered as one of the most challenging and time consuming tasks in petroleum engineering disciplines, it has important implications on decision-making, planning production and processing of facilities. In Petroleum Development Oman (PDO), which is the major petroleum company in Oman, production forecast provides a technical input basis for the economic decisions throughout the exploration and production lifecycle. Reservoir engineers spend more than 250 days per year to complete this process. PDO Forecast Management System (FMS) was introduced to transform the conventional forecasting of gas production. Employing the latest state-of-the-art technologies in the field of data management and machine learning (ML), PDO FMS aims at optimizing and automating the process of capturing, reporting, and predicting hydrocarbon production. This new system covers the full forecast processes including long and short-term forecasting for gas, condensate, and water production. As a pilot project, PDO FMS was deployed on a cluster of 272 wells and relied on agile project management approach to realize the benefits during the development phase. Deployment of the new system resulted in a significant reduction of the forecasting time, optimization of manpower and forecasting accuracy.
阿曼石油开发预测管理系统
生产动态预测是石油工程学科中最具挑战性和最耗时的任务之一,它对设施的生产和加工决策、规划具有重要意义。阿曼石油开发公司(PDO)是阿曼主要的石油公司,产量预测为整个勘探和生产生命周期的经济决策提供了技术投入基础。油藏工程师每年要花费250多天的时间来完成这一过程。引入PDO预测管理系统(FMS)对传统的天然气产量预测进行了改造。PDO FMS采用数据管理和机器学习(ML)领域的最新技术,旨在优化和自动化捕获、报告和预测油气产量的过程。这套新系统涵盖了天然气、凝析油和水产量的长期和短期预测。作为一个试点项目,PDO FMS部署在272口井的集群上,并依靠敏捷项目管理方法在开发阶段实现了效益。新系统的部署大大缩短了预测时间,优化了人力资源,并提高了预测的准确性。
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