Method to Predict Static Reservoir Pressure of HPHT Onshore Deep Gas Reservoir through WHP Surveillance: Case Study of S Gas Field in South Sumatra
Keywords:
static reservoir pressure, wellhead pressure, SBHP, HPHT deep gas reservoir, pressure-square, pseudo-pressureAbstract
S field is a gas producing field in South Sumatra that has been producing since 2010. It accounts for 100% of the block’s gas production. Despite its important role, it only has 4 static bottom-hole pressure data which were acquired during initial well completion in 2004, and CPP shut-down in 2014, 2018, and 2019.
Reservoir pressure data is very important for reserves update, reservoir simulation, surveillance, and forecasting. Reservoir pressure data is typically analyzed from Static Bottom Hole Pressure (SBHP) surveys after the well reach stabilized shut-in pressure. However, there is a multitude of risks and challenges involved in conducting SBHP survey jobs, such as high pressure & temperature (HP/HT), high H2S content, deep well, production loss, government’s approval, and high overall costs.
In order to obtain reservoir pressure data while reducing risk and cost, a method is introduced to get SBHP data from well head pressure (WHP) data during shut-in time by using pressure data correlation during latest SBHP and WHP records. In this case study, the method consists of 4 main steps: (1) Interpolate missing data from SBHP or WHP records; (2) Determine the static pressure period; (3) Plot WHP and SBHP records to determine the suitable correlation; (4) validate correlation with actual data. Three different gas-pressure approaches (pressure, pressuresquare, and pseudo-pressure) were used to get the most suitable static BHP correlation.
This paper will discuss the operational challenges, concept & procedure of proposed method, comparison, and validation result of each correlation. This method is proven to be applicable with every gas-pressure approaches with degrees of error less than 2%. In the future, this method can benefit gas field operation & reservoir monitoring activities to be more cost-efficient, with potential savings up to USD 125,000 for each planned SBHP survey job.
