Source Quality Variations Tied to Sequence Development in the Monterey and Associated Formations, Southwestern California
Published:January 01, 1993
Kevin M. Bohacs, 1993. "Source Quality Variations Tied to Sequence Development in the Monterey and Associated Formations, Southwestern California", Source Rocks in a Sequence Stratigraphic Framework, Barry J. Katz, Lisa M. Pratt
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The occurrence and hydrocarbon potential of the source rocks in the Monterey Formation (Miocene) are strongly controlled by stratigraphic and geographic position. The major shifts in the geochemical properties of the rocks occur at sequence boundaries or downlap surfaces; there are systematic variations in source quality within the sequences and sequence sets. Source richness (total organic carbon content) tends to be moderate in the lowstand systems tracts, increasing to a maximum around the mid-sequence downlap surface, and relatively low in the highstand systems tracts. Source quality in this setting is a function of the organic-sulfur content of the kerogen; quality is generally higher in the lowstand systems tracts and lower in the highstand systems tracts. Both richness and quality vary strongly at the sequence-set scale: the thin depositional sequences in the transgressive sequence set have the largest total organic carbon contents and lowest quality (highest sulfur) rocks.
The major source potential is in specific mud rock lithofacies (phosphatic shales and carbonaceous marls). These source facies are diachronous across the basins of Santa Maria and Santa Barbara Channel. The time-transgressive nature of these lithofacies units across the various subbasins make it essential to employ the physical surfaces used by sequence stratigraphy to properly correlate among outcrops and wells and to decipher the distribution of source potential. A sequence stratigraphic framework allows comparison of the geochemical measurements of time-equivalent rocks; this portrays genetic relations that can reveal depositional processes and enable construction of predictive models.