As operators move towards intelligent wells and fields, data management systems need to be adapted to support the transformation. With technology advancements and a growing network of sensors that enable faster and higher frequency data gathering, there is a need to sustainably scale data management systems to the level required to handle higher volumes of data and faster processing response. The most comprehensive systems, however, are those that support efficient decision making.
A Middle Eastern operator embarked on a project to enhance the existing well integrity data management system to add new capabilities and extend the system to other fields in the Arabian Gulf. The updated well integrity management standards were also incorporated to reflect the operator's latest business principles.
The system was further integrated with a geographical information system and well integrity business workflows were developed. The system automatically monitors data and sends notifications on abnormal well conditions. This is being supported by a single repository of all necessary data, historical inspection, pressure trends and well intervention histories.
Through continuous monitoring of operating conditions by the system and automatic task assignment when conditions indicate the rise of well problems, engineers can work more proactively and manage a growing number of assets. Automated monitoring relieves engineers from the efforts previously exerted on manual processes and allows them to focus on the engineering analysis. Having a single repository with historical inspection, safety critical equipment test data, full pressure trends and well intervention histories, provides a wealth of information from which to make informed decisions.
A benefit of having such methodology, from a management viewpoint, is that there is a common approach to well integrity indicators and key performance indicators for all assets. This allows benchmarking from field to field so that a consistent decision making approach can be made and resources of different types properly focused on those places where the challenges and demands are higher. In a period where the industry has gone through some substantial rationalization, the fact that staff can be assigned to different assets through the use of a common system with which they are familiar helps them to quickly understand, analyze and tackle well problems.
This paper examines the application of intelligent software analytics and a robust system to optimize resources and enhance efficiency and performance. By collecting a wider range of data with increased frequency and applying intelligent software analytics, the operator has been able to greatly improve the asset management coverage, thus improving efficiency and performance; satisfying regulatory requirements and achieving production targets.