Tailoring Geochemical Production Monitoring for Tight Reservoirs That Contain Migrated Oil
Production allocation relies on identifying the distinct fingerprint of the oil in different reservoir flow units. Ideally, this is accomplished using end-member oil samples produced from each pay zone, but those kinds of samples generally are not available from tight unconventional reservoirs. Instead, extracts obtained from core samples using solvents typically are used as proxies. However, those extracts typically contain producible oil and immobile fluids (e.g., bitumen; oil dissolved in kerogen) whereas produced fluids are commingled mixtures of the most mobile fluid in each pay zone. The composition of fluids produced from reservoirs with relatively homogeneous fluid mobility generally does not change (i.e., production fractionation is constant). But recent studies demonstrate that pro- duction allocation is more challenging using as end members the extracts obtained from core samples selected in source-rock reservoirs (Liu et al., 2017; Jweda et al., 2017; Kornacki et al., 2017, 2018). In hybrid or tight sandstone/siltstone unconventional plays, quasi-conventional reservoir beds com- monly contain different mixtures of migrated oil and gas. The variable reservoir quality, timing of HC charge, and production fractionation in heterogeneous flow units means produced oil and gas samples are complex mixtures that flowed from distinct stacked pay zones that repeat across the reservoir in- terval. This greatly hinders the use of reservoir geochemistry tools to monitor and allocate production. Designing effective reservoir geochemistry programs in these types of rocks requires careful planning to adequately fingerprint the oil in pay zones that contribute to the production stream. Here we describe the integration of information about reservoir quality and source-rock type and maturity with geochemical data measured on core extracts and produced fluids to identify the end members required to allocate samples produced from tight reservoirs that contain migrated fluids. We have ap- plied this workflow to several unconventional plays that contain variable amounts of migrated fluids. We will discuss examples from (i) Montney reservoirs, where updip migration and basin uplift have impacted reservoir fluids, (ii) Wolfcamp reservoirs in the Midland Basin, and (ii) the Austin Chalk play, where the maturity of Eagle Ford source rocks does not explain the gravity of oil in the Austin Chalk. In all cases, identifying oil-generating zones, migrated oil reservoirs, and ‘barren’ zones is critical to selecting end members. This can be done using source rock data and wireline log interpretations. Careful sample handling and extraction of center-cut core plugs to preserve volatile HC compounds allows gasoline-range and mid-range source and maturity parameters to be measured using HRGC data. In reservoirs like the Montney with a wide range of pore throats, different types of fluids are present in lithofacies with different pore throat sizes. Integrating poroperm, MICP data, and core de- scriptions helps identify end member fluids and the contribution of each pay zone to well production streams (i.e., geochemical flow units). Slope factor analysis, estimates of excess methane, and mud gas/produced gas C isotopic data also help us understand the origin of complex produced fluids.
AAPG Datapages/Search and Discovery Article #90349 © 2019 AAPG Hedberg Conference, The Evolution of Petroleum Systems Analysis: Changing of the Guard from Late Mature Experts to Peak Generating Staff, Houston, Texas, March 4-6, 2019