Abstract
Subsurface data management is one of the prime challenges confronting today's E&P industry. Oil & Gas companies are generating substantial amount of data in E&P operations to achieve their strategic goals. The fact that E&P companies are using multi-vendor technologies makes the case of standard procedures, consistent nomenclature, and data synchronization even more compelling to achieve the uniformity of data and related mnemonics across their databases. This in-turn maximizes the efficiency & potential of existing organizational resources along with facilitating the instant data access & data sharing among common end-users (geologist, petrophysicist, geophysicist etc.).
United Energy Pakistan, formerly known as BP Pakistan, has a hybrid environment of multi-vendor technologies supporting its operation requirement of data and information management and archival. Its assets have a rich heritage, starting nearly four decades ago when an American E&P company, Union Texas Pakistan, initiated operations in Pakistan. Since then, several changes and a shift in ownership several times has resulted challenges to manage the assets and underlying data. Corporate Data Governance and ManagementProject was embarked to address geoscience end user challenges regarding access to validated data and cleaning of working environment. The journey began with a data management maturity assessment few years ago. This helped to identify gaps in the existing data management processes and systems. An integrated roadmap was developed to bridge the gaps with identified digital initiatives and solutions. A vendor neutral and technology agnostic approach was used to perform the site assessment.
A conformance study, prior to the commencement of project, was conducted to assess the "Current State" of G&G Working project databases and to articulate the "Future State" with special emphasis on providing centralized, quality assured and integrated data environment. The study highlighted the key areas of Geoscience working environment that require improvement. Some of the key findings of study indicated huge number of working projects, data dissemination, Lack of Standards, incompleteness, inadequate dataflow mechanism and procedures, data redundancy, and inability of data search and access.
