The Value of Regional Assessments of Subsurface Pressure Models: An Application to Offshore Mexico

Global datasets are useful tools in the petroleum industry regardless of the maturity of a basin (e.g. Frontier to Mature). With the recent popularity and emergence of machine learning in the oil and gas industry there has been a renewed appreciation of the importance of global and regional datasets. This is in part due to the fact that when implementing various machine learning codes, it is apparent that the availability of training data and the quality control (sense-checking) of the outcomes play an important role on the validity of the algorithms ( Naeini and Prindle, 2018 ).

In this paper we introduce one concept of a regional study that focuses entirely on subsurface pressure assessment and we seek to highlight how these types of studies can be of high value importance throughout the entire exploration, development and production cycle ( Edwards and O'Connor, 2015 ). We focus particularly on the value of regional datasets viewed as analogous information to help de-risk new acreage for example, in the largely un-explored deep-water, Offshore Mexico acreages.