Koroteev, Dmitry Anatolyevich (Schlumberger) | Dinariev, Oleg (Schlumberger) | Evseev, Nikolay (Schlumberger) | Klemin, Denis Vladimirovich (Schlumberger R&D Inc.) | Safonov, Sergey (Schlumberger) | Gurpinar, Omer M. (Schlumberger) | Berg, Steffen (Shell Global Solutions International BV) | vanKruijsdijk, Cor (Shell) | Myers, Michael (Shell) | Hathon, Lori Andrea (Shell International E&P Co.) | de Jong, Hilko (Shell Oil Co.) | Armstrong, Ryan (Shell)
Fast and reliable EOR process selection is a critical step in any EOR project. The digital rock (DR) approach jointly developed by Shell and SLB is aimed to be the smallest scale yet advanced EOR Pilot technology. In this document, we describe the application of DR technology for screening of different EOR mechanisms at pore-scale focused to enhance recovery from a particular reservoir formation. For EOR applications DR brings unique capabilities as it can fully describe different multiphase flow properties at different regimes.
The vital part of the proposed approach is the high-efficient pore-scale simulation technology called Direct Hydrodynamics (DHD) Simulator. DHD is based on a density functional approach applied for hydrodynamics of complex systems. Currently, DHD is benchmarked against multiple analytical solutions and experimental tests and optimized for high performance (HPC) computing. It can handle many physical phenomena: multiphase compositional flows with phase transitions, different types of fluid-rock and fluid-fluid interactions with different types of fluid rheology. As an input data DHD uses 3D pore texture and composition of rocks with distributed micro-scale wetting properties and pore fluid model (PVT, rheology, diffusion coefficients, and adsorption model). In a particular case, the pore geometry comes from 3D X-ray microtomographic images of a rock sample. The fluid model is created from lab data on fluid characterization. The output contains the distribution of components, velocity and pressure fields at different stages of displacement process. Several case studies are demonstrated in this work and include comparative analysis of effectiveness of applications of different chemical EOR agents performed on digitized core samples.
Romushkevich, Raisa (Schlumberger) | Parshin, Anton (Schlumberger) | Miklashevskiy, Dmitry (Schlumberger) | Bayuk, Irina (Schlumberger) | Ursegov, Stanislav (PechorNIPIneft) | Safonov, Sergey (Schlumberger) | Gerasimov, Igor (PechorNIPIneft) | Law, David Hin-Sum (Schlumberger) | Taraskin, Evgeniy (PechorNIPIneft) | Konoplev, Yury (PechorNIPIneft) | Pissarenko, Dimitri (Schlumberger) | Danilenko, Alexander (PechorNIPIneft) | Chekhonin, Evgeny (Schlumberger) | Popov, Evgeny (Schlumberger) | Popov, Yury (Schlumberger) | Spasennykh, Mikhail (Schlumberger)
More than 8,500 measurements of the rock thermal properties - thermal conductivity, thermal diffusivity and volumetric heat capacity - performed on samples of different rock types from 6 terrigenous and carbonaceous heavy oil reservoirs provided the vast experimental data base for 4D reservoir modeling of thermal EOR recovery methods. The experimental results describe the essential spatial variations (more than 100%) in the thermal properties, including thermal rock anisotropy and heterogeneity, within the reservoirs, and significant temporal variations (up to 100% in most cases) in rock thermal properties that are caused by significant changes in reservoir temperature (up to 250 0C) and fluid type (steam, oil and brine) in rock pore space during the heating of reservoirs and oil production. Wide ranges in all thermal properties were determined from the measurements and important information on the correlations between thermal and other petrophysical properties (porosity, elastic wave velocities, etc.) was found. The analyses demonstrate that such spatial-temporal (4D) variations in the thermal properties could not be obtained from the literature data and the existing data base.
It was established also that the theoretical modeling of rock thermal properties in modern simulators leads to significant uncertainties in reservoir thermal properties estimation and could result in essential errors in oil production parameters evaluation. The importance of using accurate and representative experimental data on rock thermal properties in simulations of thermal EOR was illustrated by a simplified model of a SAGD process. In the cases simulated, serious influence (up to 50%) from uncertainties in each reservoir thermal properties (the thermal conductivity and volumetric heat capacity) on key outcome parameters - cumulative oil production and steam-to-oil ratio - was observed. Results demonstrated that different thermal properties influence on key production parameters in different ways. It was shown also that reliable data on the thermal properties of both pay zone and surrounding rocks are important for correct estimation of SAGD performance. In particular, the maximum influence of uncertainty in thermal properties of pay zone is established during first years while the influence of uncertainty in thermal properties of surrounding rocks increases with time monotonously. The parametric study showed that production predictions based on empirically derived thermal rock properties may significantly improve simulations and provide field operators with more realistic estimation of the project's economics.
The results demonstrate the necessity of detailed experimental investigations of the thermal properties of reservoirs and surrounding rock for the heavy oil field under development to provide necessary reliability of hydrodynamic modeling results.