Poster Abstracts 2023
Author: Omar Chaabi, Mohammed Al Kobaisi
Keywords: fluid flow through porous media, multiscale finite volume methods, MsFV, MsRSB
Module dependencies: msrsb
Multiscale finite volume methods are known to produce reduced systems with multipoint stencils which, in turn, could give non-monotone and out-of-bound solutions. We propose a novel solution to the monotonicity issue of multiscale methods. The proposed algorithmic monotone (AM-MsRSB/MsFV) framework is based on an algebraic modification to the original MsRSB/MsFV coarse-scale stencil. The AM-MsRSB/MsFV guarantees monotonic and within bound solutions without compromising accuracy for a variety of coarsening ratios; hence, it effectively addresses the challenge of multiscale methods' sensitivity to coarse grid partitioning choices. Moreover, by preserving the near null space of the original operator, the AM-MsRSB showed promising performance when integrated in iterative formulations using both the control volume and the Galerkin-type restriction operators. We also propose a new approach to enhance the performance of MsRSB for MPFA discretized systems, particularly targeting the construction of the prolongation operator. Results show the potential of our approach in terms of accuracy of the computed basis functions and the overall convergence behavior of the multiscale solver while ensuring a monotone approximate solution at all times.
Author: José Wilker Lima da Silva, Gustavo Peixoto de Oliveira
TRIL Lab, Federal University of Paraíba, João Pessoa city, Brazil
Keywords: geologic carbon storage, site qualification, storage quality map, gas injection simulation
Module dependencies: co2lab
Abstract: Several countries are boldly committed to reaching a carbon neutrality scenario by 2050. Geologic carbon storage (GCS) is a bridging technology under the broader carbon capture, utilization, and storage (CCUS) scope that now spearheads the Net Zero race. The goal of the CCUS chain is to capture the carbon dioxide (CO2) dispersed into the atmosphere, recycle it for further usage, or transport it to suitable locations through a pipeline network and inject it into deep geological formations for permanent storage. Regardless of numerous GCS projects that have succeeded around the globe, the reality of full-scale GCS projects still is very young in Brazil and part of this late advancement is due to the recent inception of their regulatory framework for this market. So far, there is only one CCUS operational project in the country, currently managed by Petrobras in Santos Basin and totally devoted to enhanced oil recovery. The database of storage, injectivity, and containment mechanisms of CO2 in potential storage sites, like saline aquifers and depleted reservoirs, is also limited. Our poster session intends to present a few mathematical models for selecting and ranking potential underground CO2 storage sites created under inspiration of quality maps, formerly used by for evaluation of reservoirs' productivity potential. We currently study a group of functionals endowed with distinct static and dynamic properties, in particular distance-to-trap weighting functions and have two main objectives in mind. First, to explain the nonlinear relationship of rock and fluid properties through rock quality estimates. Second, to grade field regions taking into account multiple structural traps featured by caprocks. The method works as a suggestive resource for convenient injection and storage loci. We implemented the models and simulations under the hood of MRST/co2lab and organized a case study over the UNISIM-I-D model, representative of the Namorado Field (Campos Basin, Brazil). Preliminary results show that the CO2 trapping rates reached by the functionals overcomes those of in-field legacy wells. The ultimate purpose of this study is to provide a knowledge base for future GCS projects in Brazil.
Author: Billal Aslam, Bicheng Yan
King Abdullah University of Science and Technology (KAUST)
Keywords: data-driven model, optimization, carbon sequestration, closed-loop reservoir management, graph based simulation
Module dependencies: upscaling, network-models, ad-blackoil, ad-core, co2lab, optimization
Large-scale CO2 injection for geo-sequestration in deep saline aquifers can significantly increase reservoir pressure, which, if not appropriately managed, can lead to potential environmental risk. Brine extraction from the aquifer has been proposed to control the reservoir pressure and increase storage capacity. Optimization of the well controls for this scenario is typically done using dynamic simulation from high-resolution geological models. Unfortunately, those models are unlikely to be adequately characterized or even unavailable in storage reservoirs. This study presents an alternative approach for closed-loop optimization of well control for CO2 injection & brine extraction management using coarse – grid network models (CGNet). In its simplest form, a CGNet can be derived from a standard 3D structured mesh (rectilinear or curvilinear) that roughly represents the storage medium's structural outline. Reservoir and well node parameters in the resulting finite-volume simulation graph are calibrated to minimize the mismatch with observed well data, such as rates and bottom-hole pressure.
In the closed–loop setting, CGNet is dynamically calibrated based on periodic observed well and saturation data from the field, which is imitated by fine-scale geological model response. Well control optimization based on NPV criteria is then performed for the subsequent short period in the calibrated CGNet. The field response from the optimized well control is then assimilated back to calibrate the CGNet and the entire process is repeated until the end of injection period. The application of this workflow on the example storage aquifer shows significant improvements in the amount of CO2 stored by injection/extraction strategies.
Author: Iain de Jonge-Anderson, Hariharan Ramachandran, Florian Doster, Uisdean Nicholson
Institute of GeoEnergy Engineering, Heriot-Watt University
Keywords: CO2 storage, traps, spill paths, seismic, Malaysia
Module dependencies: co2lab
Carbon capture and storage (CCS) will play a vital role in mitigating climate change by capturing CO2 emissions from industrial processes and power generation, preventing them from entering the atmosphere. In most instances, CCS projects involve the injection of CO2 into deep sedimentary reservoirs: either within hydrocarbon fields or saline aquifers. Our focus is on the Malay Basin, which is well-placed to become a CCS hub as it is a large, thick sedimentary basin located near to several CO2 point sources including industrial hubs along the east coast of Peninsular Malaysia and CO2-contaminent gas fields.
Part of our CO2 storage screening study has included analysis of where traps and migration pathways are, based purely on reservoir geometry. In a simple sense, as buoyant CO2 is injected into a permeable formation, it is expected to migrate upwards until an impermeable layer is found (a caprock), before then migrating along the base of this caprock along a pathway in the up-dip direction. If a structural trap is found along this pathway, CO2 will fill this trap before spilling out to another pathway in the reservoir structure.
Determining where structural traps and migration pathways exist in a system, and how they are connected, is essential for understanding how CO2 could migrate from a given injection point. However, modelling such systems can be computationally expensive and require many other geological parameters, adding complexity but reducing useability.
For this work, we have taken a quick-look approach for trap and spill path analysis using seismic mapping and tools provided in MRST-co2lab. We first used 3D seismic data from the Malay Basin to map potential CO2 storage aquifers. To determine the optimal injection locations, we used a series of light tools (MRST-co2lab, Nilsen et al., 2015) to quickly identify traps and spill paths within these maps. After export to geospatial format, we analysed these maps to determine potential injection locations for testing using vertical equilibrium modelling. The results of these models and the maps of traps and spill paths allowed us to quickly select prospective injection locations for more detailed future study.