Framework for Enhancing Asset Business Planning Process: A Niger Delta Case Study

Abstract

Accurate production forecasting is a critical input to asset development planning, reserves management, and investment decision-making. However, conventional forecasting techniques, particularly running decline curve analysis in isolation, often fail to capture the dynamic interactions among well scheduling, surface facility constraints, production deferments, crude losses, and capacity management strategies. In many African upstream assets characterised by ageing infrastructure, constrained evacuation capacity, and frequent operational disruptions, these interactions are more pronounced. These limitations contribute to increased uncertainty and reduced reliability of medium- to long-term production forecasts. This paper presents a dynamic enterprise production forecasting framework that integrates multidisciplinary workflows, rigorous data validation, and constraint-based modelling within a single forecasting environment – CypherCrescent's SEPAL Business Forecasting Solution (BFS). The proposed framework follows a structured, three-stage process: (1) preparation and validation of a standardised forecast input deck through cross-functional collaboration between subsurface, production, facilities, and commercial teams; (2) forecast execution using SEPAL Business Forecasting Solution (BFS) to simulate well forecast performance, surface constraints, operational downtime, and production deferments; and (3) iterative forecast review and implementation to ensure alignment with asset-level objectives and business planning requirements. The framework was applied to datasets acquired from producing assets in the Niger Delta, characterised by complex well-scheduling and surface-capacity constraints. Application of the framework resulted in a forecast that goes beyond conventional decline-based forecasts but also reflects subsurface properties, surface and facility constraints, and scheduled and unscheduled deferments. Integrated visualisation and diagnostic tools also enhanced transparency of constraint impacts and supported more effective cross-disciplinary decision-making. These results provide a robust foundation for more reliable production business forecasting across African oil and gas assets, enabling operators to strengthen revenue predictability and enhance strategic planning in increasingly volatile market environments.