Enhancing hydrocarbon recovery from compartmentalized reservoirs in the Gulf of Thailand require a significant number of production wells, presenting challenges in finding an economically viable development strategy. To address these challenges, regional operators have perfected their operational expertise by adopting a statistical drilling approach, as opposed to an object-based drilling method because the reservoirs are so thin that they cannot be tracked reliably with seismic anomalies, and also known to be distributed almost randomly (Ionnikoff, et al. 2011). This strategy maximizes the likelihood of encountering hydrocarbons, following the Gulf of Thailand (GoT) Petroleum Model, while minimizing development costs through the Well Factory Standard (WFS) Drilling Approach (Kaeng, et al. 2016, Ionnikoff, et al. 2011, PTTEP 2020). It involves multi-stack targeting and commingled production plans, aiming to increase hydrocarbon encounters by drilling near faults (high and tight) and within statistically inferred intervals indicating new sands. Additionally, the modified-S well path enables quick drilling and cluster development, reducing costs (Figure 1). This GoT/WFS development strategy been effectively employed to enable marginal field development program (FDP) planning over the past few decades, turning a marginal prospect into an economic project. However, as production areas in the Gulf of Thailand continue to mature and the most accessible sands have already been extracted, advancements in automation and optimization are necessary to develop the remaining resources and reserves within the economic cutoffs.
Manual preparation for a safe and resourceful FDP in mature development fields is often time-consuming and yields unoptimized outcomes. In recent years, our team has translated in-house knowledge and operational best-practice from the GoT/WFS model into mathematical equations, integrating them into our optimized and automated workflow. The core algorithm leverages Integer Linear Programming (ILP) to incorporate geological features and drilling criteria, to eventually provide a range of FDP scenarios. As projects advance to mature development stages, we developed optimization specifically for infill targeting functionality, which is the latest addition to our workflow (Chaipornkaew, et al. 2023). This represents a significant expansion from the initial focus on optimizing wellhead platform (WHP) placement only. The earlier work aimed to align optimal locations that are free of shallow anomalies with reachable targets, ensuring the shortest possible well paths (Ekkawong, et al. 2021). The combined efforts of the Chaipornkaew et al. (2023) studies and Ekkawong et al. (2021) studies, referred to as step-1 and step-2, have completed the automated workflow for FDP in mature fields, revolutionizing the FDP planning process in in the Gulf of Thailand. This system was tested in real pilot areas and has proven to be an efficient and optimized solution in complex regions with challenging fault systems and numerous existing wells.
This paper focuses on enhancing our in-house and innovative workflow into a complete end-to-end solution. We focused on two key areas: algorithm improvement and plugin development, enabling our tooling to be fully functional across large-scale production areas. The algorithm improvements include automating fault polygon generation for input preparation and refining well paths for added output flexibility (referred to as step-0 and step-3 respectively). Furthermore, we tackled the challenges of managing data flow between common subsurface interpretation software and our tooling by developing plugin connectors. This is crucial for successful deployment and easy adoption, to successfully transition from a manual to a fully automated FDP process. Our tooling has gone through many iterations of algorithm improvements in the early phase of deployment through geologically diverse dataset. These solutions are now applicable to conceptual FDP in both exploration and development projects, significantly enhancing the value of mature and marginal fields across assets in the Gulf of Thailand.
