Using New Well Logging Technology with Ultra-Sensitive Detection of Hydrocarbons to Assess Hydrocarbon Composition, Compartmentalization, and By-passed Pays

Abstract

A variety of logging technologies provide information during drilling as to the presence of hydrocarbons. However, these logging technologies do not measure hydrocarbons directly, but rather measure hydrocarbon proxies and infer hydrocarbon presence and phase based on this data. These technologies, while sophisticated can lack specificity and sensitivity when trying to accurately identify hydrocarbons. Additionally, some new technologies can monitor hydrocarbons from n-C1 (methane) to n-C8 (octane) and expand the scope of hydrocarbon detection. These new technologies can clearly detect gas range organics and can infer light oils and condensates. However, all of these technologies lack the ability to measure the heart of the oil or liquid hydrocarbon fingerprint of n-C7 (heptane) to n-C15 (pentadecane). Thus accurately characterizing and differentiating between multiple oil fingerprints becomes difficult, if not impossible, for current technologies. As such, these limitations negatively impact the ability of companies to properly assess and evaluate plays like the Eagleford that have numerous stacked liquid pays. However, advances in well logging technology now provide the ability to analyze downhole cutting samples to directly characterize the composition of hydrocarbons vertically through the prospect section. This provides the unique ability to look at a broad compound range from C2 to C20, which is significantly more expansive than the limited traditional ranges of C1-C5 or C1-C8 of most well gas logging techniques. The result is the ability to not only characterize gas and condensate range hydrocarbons, but also characterization multiple liquid or oil phase hydrocarbons contained in the stratigraphic intervals. The increased sensitivity and carbon range provides the ability to: - Clearly distinguish between various hydrocarbon phases - Distinguish multiple oil signatures - Identify by-passed pay - Infer compartmentalization - Avoid false positives from mud log data (C1-C5) for fracture or fault gases - Avoid false negatives from mud gas line monitoring for: - Under-pressured formations - Thick mud systems - Be used for 3-D evaluation field wide - Infer sulfur content of oils - Assess depositional environment, thermal maturity age, biodegradation with geochemical plots, which you cannot do with other technologies

AAPG Datapages/Search and Discovery Article #90193 © 2014 Rocky Mountain Section AAPG Annual Meeting, Denver, Colorado, July 20-22, 2014