Diagenetic reactions are characterized by mineral dissolution and precipitation. Both can occur separately or simultaneously and can involve one or more minerals. The process, either dissolution or precipitation, can vary over many orders of magnitude, from sub-millimeter to kilometer scale. The dominant scale for diagenetic purposes, however, would seem to be from millimeters (mm) to meters (m), with the mm scale more common in fine grained rocks such as shales and siltstones, and the meter scale more common in sandstones. Megascale phenomena (kilometers) appear to be related to fluid movement along faults and fractures and are associated with tectonic events and thermal anomalies.
There is also a slow, persistent, large-scale fluid movement associated with the dewatering of mudstones that begins on initial deposition and persists until effective porosity is lost (Bonham, 1980; Bjørlykke, 1983). The mechanics of this dewatering are reasonably well understood, at least relative to the chemical consequences, but it is still an area of active investigation, particularly as it may involve overpressure development in young, subsiding basins such as the Gulf Coast or the San Joaquin Basin of California. The importance of this dewatering flow is that it is pervasive, it involves huge volumes of rock, and if it becomes focused even slightly, it can concentrate large fluxes of fluid through limited volumes of rock.
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Reservoir Quality Assessment and Prediction in Clastic Rocks
This course is designed to emphasize the following topics: (1) Historical perspective on previous and current empirical, and geochemical methods of reservoir quality prediction; (2) Overview of diagenetic processes which significantly impact reservoir quality and those factors which act as major controls on those processes; (3) Proper design of a comprehensive or limited-focus predictive analysis of reservoir quality; (4) Methodologies for the accurate measurement of all major dependent and independent variables; (5) Data analysis techniques involved in quality control and the assessment of variability prior to performing multivariate regression; (6) Steps involved in the generation of a multivariate regression to insure that the model developed provides maximum accuracy using a minimum number of independent variables; (7) Case histories from a variety of settings illustrating application of the recommended approach to reservoir quality prediction.