Abstract
Deep clastic gas reservoirs, characterized by heterogenetic, low porosity and permeability rocks, and varying quantities of clay, are often drilled using oil-based mud (OBM) systems. It is well known, that presence of OBM affects surface mud gas data due to OBM contamination and drill bit metamorphism (DBM) phenomenon. The scope of this work is to identify and attempt to eliminate OBM contamination and DBM effects, therefore extracting only true formation gas response in order to identify zones of hydrocarbon potential from advanced mud gas (AMG) logging data.Enhancements in AMG analysis enabled identification of DBM while drilling by measuring artificially generated hydrocarbons, such as ethene (C2H4), the so-called cracked gas, which is not found in formation hydrocarbons. The use of the DBM detection from AMG analysis allows for the differentiation of formation hydrocarbons from artifacts induced by drilling processes. The provided workflow also aids in identifying tighter reservoir intervals, which can be particularly useful in cases of long horizontal sections. This study also presents cases, where a DBM workflow and mud gas fluid compositional data assists in estimating zones of higher porosity with hydrocarbon potential, as well differentiating between prolific and tight sections.Utilization of the workflow in exploration wells is useful in many instances to optimize formation evaluation during downhole formation testing, and subsequent drill stem test (DST) design. In addition, in development wells, the workflow can aid multi-stage fracking design and net-to-gross estimation.Harsh drilling conditions in tight abrasive rocks drilled using OBM muds introduces artificial hydrocarbons not indigenous to the formation and introduces false positive gas peaks on mud logs. Recognition and removal of such artifacts from analyses is important in an integrated formation evaluation. To-date, mud logging companies have been able to identify the effect of DBM on mud gas and often correlate the phenomena to bit degradation, which is an important indicator for drilling optimization. The authors attempt to summarize such findings into a formation evaluation process to assist in the identification and delineation of sampling, production, and stimulation of reservoir intervals.
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