--> Historical Transformation of the Petroleum System Methodology to Computerized Petroleum System Models and Linked Technologies

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Historical Transformation of the Petroleum System Methodology to Computerized Petroleum System Models and Linked Technologies

Abstract

The petroleum system methodology (PSM) evolved as geoscientists recognized the need to consider all elements (source, reservoir, seal, overburden) and processes (trap formation, generation-migration-accumulation) responsible for petroleum accumulations (Dow, 1974; Perrodon, 1992; Magoon and Dow, 1994). Although widespread acceptance was slow, industry now uses PSM because of spectacular failures of the original play fairway concept, such as the Mukluk offshore exploration well in 1984. The most important contribution of geochemistry to PSM is oil-source rock correlation to establish and map petroleum systems (Demaison and Murris, 1984; Tissot and Welte, 1987; Hunt, 1979; Bordenave, 1993). Early oil-source rock correlations were based on few geochemical parameters and simple bivariate plots. Later work emphasized chemometrics of many biomarker and isotope ratios to indicate petroleum systems and the degree of statistical certainty in each correlation (Peters et al., 2007). A milestone book (Welte et al., 1997) revealed growing capabilities of computerized basin and petroleum system models (BPSM), including migration modeling, pressure prediction, and compositional modeling of fluid and vapor compositions. Rapid development of unconventional resources since the early 2000s revitalized the links between geochemistry and BPSM (Hantschel and Kauerauf, 2009). Prior to ~2010, BPSM and associated visualization software were stand-alone tools to reduce exploration risk. However, integration of BPSM with other tools since ~2010 is a more efficient way to model the subsurface. For example, linked BPSM-seismic facies analysis-pore pressure prediction allows wells to be drilled safely and under budget (Mosca, 2018). BPSM-forward stratigraphic modeling (FSM) improves reservoir assessment using realistic predictions of lithology, migration paths, and accumulations (Tetzlaff and Priddy, 2001). BPSM-complex structural restoration improves assessment of seal integrity, reservoir continuity, and fluid properties (Neumaier et al., 2014). BPSM-FSM-probabilistic prospect assessment improves predictions of generation timing, migration paths, connectivity, and seals and enhances exploration portfolios based on risk-weighted geology. Linked BPSM models can be securely and efficiently run using Cloud technology for faster and more reliable decisions (Schlumberger, 2018).