Jess Kozman
Mr.Kozman is Southeast Asia Regional Manager at Mubadala Petroleum for Applications and Information Management in Singapore, supporting Indonesia, Malaysia, Thailand and Vietnam, with headquarters in Abu Dhabi. His team deploys geospatial technology for regulatory compliance and capacity planning in domestic business units. With experience in geophysics, IT and business intelligence, he has worked in 50 countries, 10 multi-national oil corporations, and governments on five continents, including a data management outsourcing plan for PETRONAS.

Geospatial Data Capacity for Domestic Malaysia Oil and Gas; Can it get any Bigger?
The oil and gas industry has always been known for being data driven, by the early 1990''s, exploration for domestic hydrocarbon reserve capacity in Malaysia was generating petabytes of digital data from geological and geophysical surveys in onshore and offshore oil provinces. It could be argued that oil and gas was doing "Big Data" before it became a buzz word in data management. Recently the emphasis on Big Data for oil and gas exploration has been on analytics and data mining from diverse geospatial datasets, as companies with an ageing technical workforce and increasing dependence on technology, attempt to learn in the right place and extend globally to newly accessible areas, using large volumes of acquired domestic data. The drive to maximize the domestic energy resource capacity of Malaysia and support global growth in export demand has led Malaysian energy companies to look more closely at their large volumes of geospatial data, increase the capacity for Big Data analytics, and find ways to present key metadata in a map view using advanced Geographic Information System tools. This represents a paradigm shift from technology, to a full geospatial infrastructure to support mission critical decisions. This paper presents a case study on how advanced geospatial data analytics were used at one oil and gas operator in Malaysia to improve their domestic resource management and derive the maximum benefit from a combination of datasets with large volumes, variety, velocity, and validity. The business case for using Big Data in a geospatial context was built on a need to analyse the geotechnical data that had supported successful drilling in other provinces, and apply it to projects where Mubadala Petroleum was partnered with PETRONAS in key offshore areas. Applications of geospatial Big Data include analysing, determining, and predicting the effect of rock type, fluid content, and pressure at depth on oil and gas production from offshore fields. The results of the Big Data analytics were made available to geotechnical users through a geospatial interface using a query-based table of contents and a Web-based service oriented architecture.
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