Background
As Ghana's oil and gas industry continues and seeks to expand, the accurate measurement of fluid flow is crucial for effective production surveillance and monitoring. Conventional flow metering systems are often expensive and face challenges in maintaining accuracy in diverse operating conditions. More so, given the recent reduction in gross production in the last few years , accuracy and reliable measurements are key elements required to understand the bottlenecks that face the industry. This project proposes the implementation of Virtual Flow Metering (VFM) technology as an innovative and cost-effective solution to address these challenges, providing accurate real-time flow measurements for production surveillance in Ghana's oil and gas sector.
Objectives
- Implementation of Virtual Flow Metering (VFM): Deploy advanced algorithms and machine learning models to develop and integrate a Virtual Flow Metering system that can accurately estimate fluid flow rates in real-time without the need for physical flow meters.
- Cost-Effectiveness: Assess the economic feasibility of VFM technology compared to traditional flow metering systems, considering both initial implementation costs and long-term maintenance expenses.
- Adaptability to Diverse Operating Conditions: Develop and optimize the VFM system to function reliably in the varying and challenging operating conditions of Ghana's oil and gas fields, ensuring accuracy across different fluid compositions and flow regimes.
Proposed Method
The project will involve the development and integration of machine learning algorithms trained on historical and real-time data from Ghana's oil and gas production facilities. Advanced data analytics will be employed to optimize the VFM system's accuracy and reliability. Additionally, field testing will be conducted to validate the performance of the VFM system under actual operating conditions.