DIET: An Integrated Approach of Getting the Right Data and Maximizing Its Value

Well and reservoir surveillance data gathering activities can present a number of logistical challenges and operational risks associated with well intervention work, especially in offshore sour gas fields. This paper describes an approach adopted by RasGas Company Limited (RasGas) to reduce these risks by implementing a workflow that facilitates full integration of the acquired data to maximise its value and improve the understanding of well/reservoir performance. Hence, the workflow is used to arrive at a need-based strategy to plan, design and execute yearly well/reservoir surveillance programmes. The need for early well and reservoir performance data when a new gas field is placed on production often necessitates a calendar-based and broadly applied surveillance programme to develop reservoir deliverability and well productivity trends across the field. These baseline data are used to proactively identify and quantify potential threats to well productivity and production sustainability from issues such as skin build up from scale or condensate banking, unexpected formation water production, corrosion damage, etc. Once the sufficient baseline data set has been acquired, there is a need to develop an optimum approach towards well and reservoir surveillance programmes. This ensures that surveillance programme is focused on delivering truly needed data while reducing the risks inherent to well intervention activities. RasGas achieved this optimisation through development of a workflow called “DIET” (Data Integration and Evaluation Technique). Implementation of DIET has significantly reduced the reliance on a set-frequency logging strategy, thus reducing overall well intervention job counts, costs and risks. In addition to integrating all relevant data for single well evaluation, the DIET workflow is also being expanded to enable field-wide data integration.