Africa (Sub-Sahara) Aminex Petroleum Egypt (APE), a subsidiary of UK-based Aminex, discovered oil at its South Malak-2 (SM2) well on the West Esh el Mellaha-2 concession in Egypt. Based on the findings at SM2, a full field development program will be presented to the Egyptian authorities and the joint venture partners before commercial development.
Fatehgarh reservoirs in Aishwariya field, located in Barmer Basin of Rajasthan India, have very high CO2 content in reservoir fluid. A procedure was developed earlier to model the impact of reservoir CO2 on waterflood, polymer flood and ASP flood (
The objective of this work was to validate the modelling procedure developed to predict the produced gas rate in such a system with very high amount of CO2 in reservoir fluid.
A live oil coreflood experiment was carried out using 12 inches long Bentheimer core under Aishwariya reservoir pressure and temperature conditions. After saturating the core with live oil, the core was water flooded with brine for ~3.7 pore volumes. Produced gas volume was measured at different times so as to generate gas production profile.
Two different simulation techniques were used to simulate the experiment and match the gas production profile. First technique was using a compositional simulator with EOS based PVT while the other technique was using an "advanced processes simulator" modeling the component distributions based on partitioning coefficients. Both methods could successfully capture the production of gas from both liquid streams; oil and water and a reasonable match for the produced gas could be obtained.
The approach developed to simulate impact of CO2 on different aqueous based flooding processes in Aishwariya field was validated by matching the coreflood experiment carried out under actual Aishwariya reservoir conditions. It helped to confirm confidence in performance prediction of aqueous based flooding mechanisms planned in Aishwariya field despite the presence of significant amount of CO2.
The paper presents history match of unconventional produced gas profile of a coreflood carried out under Aishwariya field conditions with very high amount of dissolved CO2. The proposed method can be applied to estimate produced gas rate in other fields with very high amount of CO2 in reservoir fluid.
Mancilla-Polanco, Adel (University of Calgary) | Johnston, Kim (University of Calgary) | Richardson, William D. L. (University of Calgary) | Schoeggl, Florian F. (University of Calgary) | Zhang, Y. George (University of Calgary) | Yarranton, Harvey W. (University of Calgary) | Taylor, Shawn D. (Schlumberger-Doll Research)
The phase behavior of heavy-oil/propane mixtures was mapped from temperatures ranging from 20 to 180°C and pressures up to 10 MPa. Both vapor/liquid (VL1) and liquid/liquid (L1L2) regions were observed. Saturation pressures (VL1 boundary) were measured in a Jefri 100-cm3 pressure/volume/temperature (PVT) -cell and blind-cell apparatus. The propane content at which a light propane-rich phase and a heavy bitumen-rich (or pitch) phase formed (L1/L1L2 boundary) was visually determined with a high-pressure microscope (HPM) while titrating propane into the bitumen. High-pressure and high-temperature yield data were measured using a blind-cell apparatus. Here, yield is defined as the mass of the indicated component(s) in the pitch phase divided by the mass of bitumen in the feed. A procedure was developed and used to measure propane-rich-phase and pitch-phase compositions in a PVT cell.
Pressure/temperature and pressure/composition phase diagrams were constructed from the saturation-pressure and pitch-phase-onset data. High-pressure micrographs demonstrated that, at lower temperatures and propane contents, the pitch phase appeared as glassy particles, whereas at higher propane contents and temperatures, it appeared as a liquid phase. Ternary diagrams were also constructed to present phase-composition data. The ability of a volume-translated Peng-Robinson cubic equation of state (CEOS) (Peng and Robinson 1976) to match the experimental measurements was explored. Two sets of binary-interaction parameters were tested: temperature-dependent binary-interaction parameters (SvdW) and composition-dependent binary-interaction parameters (CDvdW). Models derived from both types of binary-interaction parameters matched the saturation pressures and the L1L2 boundaries at one pressure but could not match the pressure dependency of the L1L2 boundary or the measured L1L2 phase compositions. The SvdW model could not match the yield data, whereas the CDvdW model matched yields at temperatures up to 90°C.
Hydrocarbon-reservoir-performance forecasting is an integral component of the resource-development chain and is typically accomplished using reservoir modeling, by means of either numerical or analytical methods. Although complex numerical models provide rigorous means of capturing and predicting reservoir behavior, reservoir engineers also rely on simpler analytical models to analyze well performance and estimate reserves when uncertainties exist. Arps (1945) empirically demonstrated that certain reservoirs might decline according to simple, exponential, hyperbolic, or harmonic relationships; such behavior, however, does not extend to more-complex scenarios, such as multiphase-reservoir depletion. Because of this limitation, an important research area for many years has been to transform the equations governing flow through porous media in such a way as to express complex reservoir performance in terms of closed analytical forms. In this work, we demonstrate that rigorous compositional analysis can be coupled with analytical well-performance estimations for reservoirs with complex fluid systems, and that the molar decline of individual hydrocarbon-fluid fractions can be expressed in terms of rescaled exponential equations for well-performance analysis. This work demonstrates that, by the introduction of a new partial-pseudopressure variable, it is possible to predict the decline behavior of individual fluid constituents of a variety of gas/condensate-reservoir systems characterized by widely varying richness and complex multiphase-flow scenarios. A new four-region-flow model is proposed and validated to implement gas/condensate-deliverability calculations at late times during variable-bottomhole-pressure (BHP) production. Five case studies are presented to support each of the model capabilities stated previously and to validate the use of liquid-analog rescaled exponentials for the prediction of production-decline behavior for each of the hydrocarbon species.
An accurate description of the microemulsion-phase behavior is critical for many industrial applications, including surfactant flooding in enhanced oil recovery (EOR). Recent phase-behavior models have assumed constant-shaped micelles, typically spherical, using netaverage curvature (NAC), which is not consistent with scattering and microscopy experiments that suggest changes in shapes of the continuous and discontinuous domains. On the basis of the strong evidence of varying micellar shape, principal micellar curves were used recently to model interfacial tensions (IFTs). Huh’s scaling equation (Huh 1979) also was coupled to this IFT model to generate phase-behavior estimates, but without accounting for the micellar shape.
In this paper, we present a novel microemulsion-phase-behavior equation of state (EoS) that accounts for changing micellar curvatures under the assumption of a general-prolate spheroidal geometry, instead of through Huh’s equation. This new EoS improves phase-behavior-modeling capabilities and eliminates the use of NAC in favor of a more-physical definition of characteristic length. Our new EoS can be used to fit and predict microemulsion-phase behavior irrespective of IFT-data availability. For the cases considered, the new EoS agrees well with experimental data for scans in both salinity and composition. The model also predicts phase-behavior data for a wide range of temperature and pressure, and it is validated against dynamic scattering experiments to show the physical significance of the approach.
Compositional simulators conventionally use Li's correlation to approximate the critical temperature (
We here propose to replace Li's correlation by a rigorous calculation of
In order to address the observation that gas/oil relative permeability curves tend to straight lines when approaching to the critical point, a second level of interpolation with respect to the IFT is applied within the phase envelope between miscible and immiscible three-phase models. Continuity is, by construction, guaranteed at any possible phase-state transition.
The proposed relative permeability model is first tested standalone (i.e., on a single cell) with different hydrocarbon mixtures, by analysis of the dependent parameter (true or fictitious IFT) and the relative permeabilities at different
The model is secondly implemented in our In-House Research Reservoir Simulator (IHRRS), and tested on a synthetic 2D cross-section undergoing near-critical gas injection. We observe that with conventional models based on Li's correlation, discontinuities in the relative permeability model when crossing the phase envelope occur, as well as spurious phase flipping. No such unphysical behavior is observed with the proposed approach, while requiring the same input data.
There is of course a computational cost involved in properly calculating
In this work, we present the development of a compositional simulator accelerated by proxy flash calculation. We aim to speed up the compositional modeling of unconventional formations by stochastic training.
We first developed a standalone vapor-liquid flash calculation module with the consideration of capillary pressure and shift of critical properties induced by confinement. We then developed a fully connected network with 3 hidden layers using Keras. The network is trained with Adam optimizer. 250,000 samples are used as training data, while 50,000 samples are used as testing data. Based on the trained network, we developed a forward modeling (prediction) module in a compositional simulator. Therefore, during the simulation run, the phase behavior of the multicomponent system within each grid block at each iteration is obtained by simple interpolation from the forward module.
Our standalone flash calculation module matches molecular simulation results well. The accuracy of the trained network is up to 97%. With the implementation of the proxy flash calculation module, the CPU time is reduced by more than 30%. In the compositional simulator, less than 2% of CPU time is spent in the proxy flash calculation.
The novelty of this work lies in two aspects. We have incorporated the impacts of both capillary pressure and shift of critical properties in the flash calculation, which matches molecular simulation results well. We developed a proxy flash calculation module and implemented it in a compositional simulator to replace the traditional flash calculation module, speeding the simulation by 30%.
Despite the great interest and importance of modeling hydrocarbon production from tight oil reservoirs, the thermodynamic stability of multicomponent mixtures with capillary pressure has not been studied sufficiently. This paper introduces a practical algorithm for phase stability analysis of multi-component mixtures with capillary pressure. The capillary pressure is determined from a realistic saturation-dependent function which is representative of pore size distributions as well as other petrophysical properties such as wettability and water saturation. The new stability procedure is coupled with flash calculations. Therefore, the phase saturations and compositions of the mixture are also provided in addition to the stability condition once the solution is converged. The significance and robustness of the new method is shown in several examples with realistic tight oil and gas-condensate mixtures.
A novel formulation for modeling nonlinear reactive-compositional transport comprising of complex phase behaviors with chemical and thermodynamic interactions is presented. The precipitation/dissolution of minerals during reactive flow in subsurface reservoirs is modeled in the newly designed simulation framework. This framework uses molar formulation with a consistent reduction of governing mass balance equations from component to element mole fractions. The thermodynamic phase behaviour is extended by including the chemical equilibrium reactions in the multiphase thermodynamic flash. This allows for a general treatment of chemical and thermodynamic equilibrium in a fully couple and implicit manner. The governing component conservation equations are reduced to element conservation equations using the Equilibrium Rate Annihilation matrix. The element composition of the mixture serves as an input for these computations whereas the output is fractions of components in each phase, including solids. To solve the resulting nonlinear element based governing equations, we use the Adaptive Operator-Based Linearization (OBL) approach where the governing equations are formulated in terms of space and state-dependent parameters. The proposed framework is utilized for modeling of several challenging flow and transport problems with dissolution and precipitation reactions. This is the first time when a multiphase multicomponent flash using element fractions as an input is coupled with an element balance compositional formulation and validated for multidimensional problems of practical interest. In addition, an efficient parametrization using adaptive OBL approach improves both robustness and performance of complex reactive-compositional flow and transport.
Pan, Huanquan (Stanford University) | Imai, Motonao (Japan Oil, Gas and Metals National Corporation/Waseda University) | Connolly, Michael (Stanford University) | Tchelepi, Hamdi (Stanford University)
Robust and efficient multiphase flash calculations are crucial in compositional and thermal simulations for complex fluid systems in which three or four phase may co-exist. Solution of the Richford-Rice (RR) equations is an important operation in the multiphase flash. The Newton method generally does not converge during solution of the RR equations unless very good initial values are provided. In this paper, the solution of the RR equations is formulated as a minimization of a convex function problem. For the first time, we use a trust-region (TR) method to solve the RR equations through minimization of the convex function. The Hessian matrix of the convex function is always positive-definite, and the TR-based solver guarantees convergence. The key to successful implementation is to determine the relaxation parameter in the Newton update. We select this relaxation parameter to meet the boundary of the objective function and to ensure an adequate step length. We tested the RR solver for three and four phase RR problems in the construction of phase diagrams. The test cases are representative of complex fluid systems encountered in enhanced oil recovery, including injection of CO2 into low temperature reservoirs and steam injection into heavy oil reservoirs at elevated temperatures. We performed tens of millions of multiphase flash computations, the results of which reveal our RR solver to be robust, efficient, insensitive to initial values, and capable of handling negative phase amounts. We also evaluated the effect of the initial values on convergence and recommend methods to estimate the initial values in our RR solver. In summary, our RR solver greatly improves the multiphase flash calculations and strengthens the coupling of phase equilibrium calculations to the governing equations in multiphase compositional and thermal simulation.