--> Abstract: Modern Interpretation and Integration by Modeling Near-Surface Geochemical Data, by Gary K. Rice and John Q. Belt; #90914(2000)

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Gary K. Rice1, John Q. Belt1
(1) GeoFrontiers Corporation, Rowlett, TX

Abstract: Modern Interpretation and Integration by Modeling Near-Surface Geochemical Data

Conventional interpretation of near-surface, geochemical data emphasizes highest concentrations, or "anomalies". Conventional integration involves "stacking" multiple geochemical data sets. Stacked areas, with the most anomalous data, are considered more prospective. This integration predicates all hydrocarbons, both light hydrocarbons (C1-C6) and mid-weight hydrocarbons (C10-C20), non-selectively use the same migration pathways.

Modern modeling concepts attempt to explain data patterns for different geochemical data sets. Understanding the mechanics of structural geology for generating fracture patterns is imperative for proper interpretation and integration of geochemical data.

Examples illustrate these modern modeling concepts by using light and mid-weight hydrocarbon data which produce different surface patterns. Two "non-stacking" anomalous surface patterns would confuse conventional integration. However, modern interpretation and integration concepts do not stack, or correlate, different geochemical patterns. Instead, each pattern is integrated with geological and seismic data to determine different migration pathways.

Offshore Example: Offshore data, Gulf of Mexico, illustrates the different surface expressions from light and mid-weight hydrocarbon data. 3D seismic data helps identify larger migration pathways, such as faults, from the reservoir to the near-surface. Integrating this information offers detailed, specific information about possible petroleum reservoirs at depth.

Land Examples: The same concepts, applied on land, are illustrated by examples from the Eastern Shelf, Midland Basin. Hydrocarbons migrating along larger and smaller fractures can be differentiated. Larger fractures, identified from mid-weight (C10-C20) hydrocarbon data, help detect lithofacies (sand/clay) boundaries near reservoir formations. These examples illustrate ways to extract valuable geological information from different geochemical data sets.

AAPG Search and Discovery Article #90914©2000 AAPG Annual Convention, New Orleans, Louisiana