Publications

Tunu giant gas field is located in the Mahakam delta, East Kalimantan, Indonesia, consists of two hydrocarbon zones which are the shallow zone (150 m-2000 m TVDSS) and the main zone (2000 m-5000 m TVDSS). Initially the shallow gas zone was considered as drilling hazard, yet nowadays it contributes almost 60% of Tunu production. The exploitation of Tunu Shallow Zone (TSZ) has been commercially conducted with aggressive drilling operations since 2010 to fight back the field's natural decline.

The identification of TSZ shallow gas relies heavily on robust seismic-based AVO (Amplitude versus Offset) methods, with the aim of transforming over 20,000 scattered seismic anomalies of potential gas reservoirs into economically viable development wells. Until 2023, more than 400 wells have been drilled to produce hydrocarbon gas in TSZ. Gas identification in TSZ yielded a 75% success ratio with the biggest challenge consists of distinguishing gas anomalies from coal with variations of seismic quality, reservoir trap geometry and abundant coal which leads into uncertainties in gas identification and net pay prediction. To improve the success ratio of gas reservoir prediction, a detailed analysis using angle-stack attributes alongside AVO to distinguish gas from non-gas patterns based on surrounding well results are needed. However, this detailed and time-intensive analysis requires significant challenges when associated with the aggressive drilling schedule (>30 wells/year).

To accelerate the analysis process, an in-house Python-based web application called TSZ Web-Apps was designed to provide statistical calibration to simplify and streamline the target maturation process. This centralized application enables the analysis of multiple seismic-driven prospects on a single webpage includes AVO gas and non-gas pattern discrimination also ensures those analysis and insights are easily accessible, sustainable, and manageable across multiple users. By implementing TSZ Web-Apps, the prospect maturation process only requires half the time compared to conventional methods and it significantly enhances the efficiency of evaluating seismic-driven prospects. This application can be an example of how an open-source library with almost zero cost can be a game-changer on a mature and complex field development like Tunu Field.