UC Santa Barbara
Geologic control of natural marine hydrocarbon seep emissions, Coal Oil Point seep field, California
- Author(s): Leifer, Ira
- Kamerling, Marc J.
- Luyendyk, Bruce P.
- Wilson, Douglas S.
- et al.
Published Web Locationhttps://doi.org/10.1007/s00367-010-0188-9
High-resolution sonar surveys, and a detailed subsurface model constructed from 3D seismic and well data allowed investigation of the relationship between the subsurface geology and gas-phase (methane) seepage for the Coal Oil Point (COP) seep field, one of the world’s largest and best-studied marine oil and gas seep fields, located over a producing hydrocarbon reservoir near Santa Barbara, California. In general, the relationship between terrestrial gas seepage, migration pathways, and hydrocarbon reservoirs has been difficult to assess, in part because the detection and mapping of gas seepage is problematic. For marine seepage, sonar surveys are an effective tool for mapping seep gas bubbles, and thus spatial distributions. Seepage in the COP seep field occurs in an east–west-trending zone about 3–4 km offshore, and in another zone about 1–2 km from shore. The farthest offshore seeps are mostly located near the crest of a major fold, and also along the trend of major faults. Significantly, because faults observed to cut the fold do not account for all the observed seepage, seepage must occur through fracture and joint systems that are difficult to detect, including intersecting faults and fault damage zones. Inshore seeps are concentrated within the hanging wall of a major reverse fault. The subsurface model lacks the resolution to identify specific structural sources in that area. Although to first order the spatial distribution of seeps generally is related to the major structures, other factors must also control their distribution. The region is known to be critically stressed, which would enhance hydraulic conductivity of favorably oriented faults, joints, and bedding planes. We propose that this process explains much of the remaining spatial distribution.
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