No abstract

For conventional hydrocarbon reservoirs, primary drainage capillary pressure (Pc) curve is used to quantify saturation distribution at discovery and original in-place volumes. However, for lower quality rocks (k < 10 mD), conventional centrifuge-based technique does not provide sufficient driving force to desaturate rocks close to irreducible saturation (Swir), leading to incomplete characterization of the saturation distribution. Although, most tight reservoir might not be thick enough to have water saturations (Sw) approaching Swir, accurate determination of Swir is critical as it is the endpoint for relative permeability. Uncertainty in Swir leads to uncertainty in water mobility at low Sw, water breakthrough, and modeled performance of production wells. In this work, we combine a portfolio of methods to quantify Pc for tight rocks to decrease this uncertainty. Tight outcrop plugs (0.01 mD < k < 10 mD) were thoroughly cleaned, and dried before porosity and absolute permeability measurements. Centrifuge air-brine primary drainage Pc measurements were conducted up to (i) 125-130 psi in a conventional equipment (up to 3200 RPM) using stock brine, (ii) ~250 psi in a conventional centrifuge using a heavy brine containing Cesium Formate, and (iii) 500 psi by spinning up to 10,000 RPM under overburden pressure in a high-speed centrifuge. Pc measurements were also conducted using Vapor Desorption, Digital Rock Physics (DRP), and Mercury Injection Capillary Pressure (MICP) on companion plugs. Centrifuge data were processed using Hassler-Bruner and Forbes technique, and a set of acceptable solutions were generated to quantify uncertainty. For tight rocks, Pc measurements with conventional centrifuge led to significant (~20%) uncertainty in irreducible water saturation (Swir), and thus in-place volumes. This uncertainty was reduced substantially either by incorporating high-speed centrifuge data or vapor desorption data. DRP-based calculations performed by 4 vendor labs agreed with each other, and with the experimental Pc measurements at low Pc values, but diverged significantly at high Pc. Uncertainty estimation from DRP-based Pc calculations was non-trivial, and therefore DRP-based data could not either quantify or decrease uncertainty in the in-place volumes. MICP-based measurements (scaled for interfacial tension) significantly overestimated in-place volume, as those measurements asymptotically approach Swir = 0. Vapor desorption measurements provided an anchor for Pc data at values starting 400 psi for air-brine system, and complemented the centrifuge measurements to decrease uncertainty. We combine the strengths of experimental and imaging techniques to decrease uncertainty in in-place volumes, particularly for low quality (tight) resources. Novel use of fluids and synergistic use of experimental techniques presented here significantly expand our capabilities to analyze capillarity in tight rocks.

Estimation of reservoir rock properties using multi-scale imaging of the pore structure, followed by mathematical modeling of the segmented images i.e. Digital Rock Physics (DRP) is a promising technique. However, DRP workflows are highly variable in terms of imaging tools, resolution of those tools, segmentation algorithms, handling of unresolved porosity, gridding of the resolved pore structure, and mathematical modeling of flow properties. As a result, users familiar with physical measurements of reservoir properties struggle to judge the quality of DRP data, and to incorporate DRP data in commercial workflows in a suitable manner. In this work, we present a DRP study on tight rocks (kabs < 10 mD) conducted at 4 digital vendor labs, anchored to high quality physical measurements conducted in our lab. We selected core plugs from a set of six outcrop rocks. We cleaned the plugs, measured porosity (φ) and absolute permeability (kabs), and then split the plugs in 4 quarters. Four commercial DRP labs conducted blind porosity and permeability predictions on those quarter plugs using (a) only micro-CT based tools, and (b) all the tools accessible to DRP service providers. We also compare primary drainage capillary pressure (Pc) calculated by 4 DRP vendors on quarter plugs with centrifuge based gas-water measurements conducted in-house on companion plugs. As a result of this blind study, we gained insights into workflows, strengths/weaknesses of DRP predictions carried out by 4 vendors. Various levels of physical measurements (labbased kabs, and φ data, MICP, or none) are used by different vendors to anchor DRP data. DRP predictions for porosity were from 37% to 96% of the measured values, whereas permeability is within a factor of 0.4 to 4 from the experimental measurements. At low Pc values, predictions by the 4 DRP vendors generally agreed with each other, and with experimental measurements. However, the values diverged significantly at high Pc. Based on this study, we conclude that the dominant source of error in DRP data is highly specific to a given sample, technique, or operator. A lot more uncertainty quantification is necessary to allow DRP data to be used instead of physical measurements for business decisions on tight rocks. We outline learnings for hydrocarbon resource owners and DRP data providers so that commercial workflows could benefit from DRP-based data.