Decision #001 – Research Direction

[Daya-py]

Decision #1 – Research Direction

Background

Routine production data provide valuable information about the operational behaviour of oil wells and are widely used in production surveillance and performance evaluation. These data include production rates, pressures, temperatures, choke settings, and other operational measurements collected throughout the life of a field.

While these variables are routinely monitored, they are often analysed separately or for specific operational purposes. A more integrated approach to evaluating well performance using routinely collected production data may provide a more comprehensive understanding of well behaviour and support consistent engineering assessment.

Research Direction

This project will investigate the development of an integrated framework for evaluating well performance using routine production and operational data from the Volve Oil Field.

Working title

An Integrated Framework for Multi-Parameter Well Performance Evaluation Using Routine Production Data: A Case Study of the Volve Oil Field

Motivation

The Volve dataset contains a wide range of routinely measured production and operational variables collected from multiple wells. This provides an opportunity to investigate how these measurements can be integrated into a structured framework for well performance evaluation.

The study seeks to develop a methodology that is systematic, reproducible, and applicable to routine production data.

Expected Contribution

The expected outcome of this research is an integrated framework for well performance evaluation that combines multiple production and operational parameters within a single methodology. The framework will be evaluated using the publicly available Volve dataset to demonstrate its applicability and potential value for production engineering studies.

Status

Research direction approved.