Contributions to the piezoelectric response in pseudocubic 0.3BaTiO3-0.1Bi(Mg1/2Ti1/2)O3-0.6BiFeO3 ceramics were investigated by synchrotron X-ray diffraction under electric fields. All of the lattice strain determined from the 110, 111, and 200 pseudocubic diffraction peaks showed similar lattice strain hysteresis that was comparable to the bulk butterfly-like strain curve. It was suggested that the hysteresis of the lattice strain and the lack of anisotropy were related to the complex domain structure and the phase boundary composition.

In a carbonate field, a gas injection scheme has been assessed to improve oil recovery through pressure maintenance and miscible displacement. The potential study assumed sequential application of several gas injection concepts: Raw Gas Injection (RGI) and Acid Gas Injection (AGI). Flow simulation studies of these concepts revealed a variety of compositional changes to the in-situ fluid depending on the injection scheme and composition of the injected gases. Compositional change is a common trigger of asphaltene instability; therefore, to ensure a robust gas injection development, it is important to evaluate the risk of asphaltene deposition. Due to high H 2 S concentrations in potential developments, it is difficult to take an experimental approach for evaluating gas-mixed asphaltene flow assurance. Hence, this paper will focus on one AGI scenario, and present how AGI impacts asphaltene precipitation behavior through numerical modeling analysis. Based on the asphaltene model established by applying Cubic Plus Association (CPA) equation of state (EoS), which was calibrated with the experimental measured asphaltene onset pressure (AOP), a new Binary Interaction Parameters (BIP) correlation between H 2 S and hydrocarbons was incorporated to evaluate variation of asphaltene precipitation envelope (APE) with periodical compositional change observed from the AGI flow simulation. Acid Gas (AG) was assumed to be 90mol% H 2 S and 10mol% CO 2 . The produced fluid H 2 S concentration used in this study was assumed to be~15mol%. During this study, H 2 S concentration was observed to increase up to 76mol% at a well located near AG injectors after long term flow simulation. In the APE sensitivity analysis that was independently conducted for each composition of H 2 S and CO 2 , the asphaltene model revealed the base APE shrunk as the H 2 S concentration increased while it expanded as the CO 2 concentration increased. As a result for the mixed compositions, the opposing effects on the APE offset each other; the AG addition produced a subsequent shrinking of the APE. In summary, this work supported acid gas injection from a thermodynamically asphaltene flow assurance point of view.

It is important to predict the amount of bypassed oil in EOR gasflooding since some portion of the flooded domain may be uncontacted by the injected gas due to reservoir heterogeneities residing in various scales. In this paper, we present a new method of deriving immobile and non-vaporizing residual oil saturation under miscible flood (Sorm, Hiraiwa and Suzuki 2007) from the results of CO2 coreflood experiments. We also demonstrate that Sorm is a sort of upscaled parameters able to absorb complex heterogeneous features in the finer scale. We history-matched CO2 coreflood experiments using the two different simulation models: one-dimensional (1D) homogeneous model with Sorm and two-dimensional (2D) heterogeneous model without Sorm. Both of these two models replicated secondary- and tertiary-mode CO2 coreflood experiments using core and fluid samples acquired in one of the Abu Dhabi's offshore fields. Hence we successfully obtained the Sorm based on the coreflood experiments for further use in evaluating CO2 injection in a real reservoir. In addition, we effectively modeled the core-scale heterogeneity using the X-ray computerized tomography (CT) data and pore size distribution (PSD) data derived from mercury injection capillary pressure (MICP) tests in the 2D model.

The Jurassic Plover Formation is one of two reservoirs in the Ichthys Field, North West Shelf of Australia. It consists of fluvial to shallow-marine sandstones, shales and igneous rocks. The objective of this study is to build multiple scenario-based models to optimise development planning in preparation for the upcoming production phase. We have integrated data and interpretations of thin sections, cores, well logs and seismic data to create multiple geological concepts for the field and to identify key geological uncertainties. As the reservoir is geologically complex and many uncertainties were initially identified, it is essential to single out those uncertainties which have a significant impact on the development planning. We have established the key uncertainties and optimal model design for practical use through multi-disciplinary discussions and by running sensitivity models to check the production performance. A rock type (RT) scheme has been devised based on detailed petrographic observations and justified in terms of sedimentology and diagenesis. Using the scheme, a wide range of permeability variations in the sandstones has been captured and modelled. Environments of deposition (EOD) are firstly interpreted at core and well-log scales, then upscaled to the model zone scale. The EOD interpretations are laterally extended using lithology (sandstone, shale and igneous rock) probability maps derived from quantitative seismic interpretation (QSI). Multiple EOD scenarios are generated to capture the possible range of reservoir distributions. Each EOD is characterised by a unique net-sand porosity and RT proportion based on the well data. These values are used to define multiple possible porosity trends and RT proportions, guided by the EOD maps. The distribution and quality of the reservoir sandstones have been identified as key uncertainties. Another key uncertainty is reservoir compartmentalisation, thought to be mainly caused by sheet-like igneous intrusions. Subtle seismic lineaments are regarded as possible indications of such igneous intrusions, and multiple compartmentalisation scenarios have been prepared based on our understanding of igneous activity across the field. Reservoir structure and water saturation are also recognised as key uncertainties. Integrating the key uncertainties, we have established a practical modelling workflow and built multiple scenario-based models to cover a sufficient range of geological uncertainty. The workflow is also adaptive for future history matching, enabling us to flexibly edit the model properties under geological constraints. A decision tree for development planning, which defines a series of decisions for the well sequence depending on the well results, will be prepared based on the multiple scenario-based models delivered in this study. This will enable us to prepare for any potential decision-making in advance. The development planning will be continuously optimised throughout the production phase by simply selecting the scenario-based models most in line with the well results.

In this paper, we show a new upscaling process to accurately predict the production performance of gas-condensate reservoirs, accounting for condensate banking phenomena, using a coarsely-gridded black-oil simulation model. In reservoir simulation, it has been necessary to conduct time-consuming fine-grid compositional simulation to reasonably predict the reservoir pressure profile and condensate banking near the wellbore. A newly-developed in-house program utilizes the Adaptive Local-Global Multiphase Upscaling (ALGMP) methodology developed by Nakashima et al. (2012)1. The main feature of the program is that both the entire model domain (global boundary) and local domain (well vicinity) are taken into account in the upscaling process to retain the accuracy of prediction within a relatively short computation time. The entire model domain was reflected in the form of a coarse-grid full-field model, from which a near-wellbore area of interest was extracted for fine-grid compositional modelling (using velocity-dependent relative permeability (VDRP) to represent relative permeability improvement around wellbore caused by high velocity and/or low interfacial tension (IFT)), applying common flux boundary conditions at each time-step. In the coarse-grid full-field model, mobility change is mainly due to the near-wellbore condensate drop-out observed in the fine-grid compositional model. This was reflected by an iterative upscaling of the gas-condensate relative permeability and fluid properties, using an optimization loop over the local domain, to match the well phase flow rates in the coarse-grid black-oil model with that in the fine-grid compositional model, within an acceptable margin. The developed program was applied to a real gas-condensate field model and demonstrated that the ALGMP procedure can provide well performance predictions close to the reference fine-grid simulation results with reduced computational time. The accuracy of the ALGMP procedure is higher than that of a standard single-phase upscaling approach.