Abstract
Recovery Factor Improvement (RFI) is a process to check the hydrocarbon production efficiency by incorporating the actual static and dynamic field data, as well as the way how the field being operated. This has been a common process within Shell's portfolio since 2018 (Ref; Muggeridge et al., 2013 & Smalley et al., 2009). The approach has been developed to stimulate the identification of new opportunities to increase the recovery from the existing fields and to aid the maturation of these opportunities into the Opportunity Realization Process.
There are four (4) factors that affected overall reservoir recovery factor, they are: Pressure efficiency; related to which pressure can be reduced in the reservoir as dictated by the relevant facilities and wells.Drainage Efficiency; the proportion of the in-place hydrocarbon that is pressure-connected directly to at least one producing well on a production timescale.The "secondary pay" efficiency; takes into account the volumes of poorer quality rock in which the gas remains at pressure above the lowest pressure just outside the wellbore (Pf) when the reservoir is abandoned.Cut-off Efficiency; the proportion of hydrocarbon that is lost due to non-production of the tail.This approach was applied in the dry gas Natih Reservoir fields in the PDO concession area. Before the implementation of RFI, the average recovery factor for Natih was around 70%. This was considered low for a homogenous-dry gas reservoir. The targeted Natih fields were benchmarked against each other with a total of 11 fields with similar reservoir properties. Post the benchmarking exercise, the expected field recovery factor is approximately ~90-93%. The team managed to map out the opportunities to achieve the targeted RF and identified the road map activities. The activities are mainly related to: production optimization: retubing, re-stimulation reduce drainage: infill drilling, horizontal well reduce the field intake through compression
The outcome of the mapping was then further analyzed through integrated framework to be matured as a firm-project. The new proposed activities are expected to add around 9% additional recovery to the existing fields. There will be a remaining activities which will be studied in the future, example infill wells and intelligent completions. These will close the gap to TQ and add other addition RF of 11-13%.
As conclusion, the RFI was seen as a structured approach to better understanding the field recovery factor based on the integrated surface and subsurface data with a robust analysis to trigger opportunity identification linked to RFI elements. It is similar concept as sweating the asset by generating limit diagram for each recovery mechanism & the road map to achieve the maximum limit. This paper will highlight the Natih Fields RFI analysis, highlighting the key learning and challenges.
Observations on and use of curves of current dimensionless potential versus recovery factor calculated from models of hydrocarbon production systems
