Miscible Gas Injection EOR Complex Challenges – A CCUS Hub Approach to Unlock Value for a Multi Reservoir Onshore Field

Miscible CO2 flood is a well-established proven EOR recovery mechanism. There have been a large number of CO2 EOR developments worldwide, in both carbonate and clastic reservoirs. Potential control or influence factors on incremental production and incremental recovery over water flood are well documented in the published literature. Some of the published CO2 EOR developments have reported relatively high incremental recoveries. ADNOC is a leader in miscible gas injection EOR in carbonate reservoirs. There are a number of ongoing miscible gas injection EOR developments within its portfolio contributing a significant amount of production. Miscible CO2 flood is a key EOR development for ADNOC. Following intensive screening studies and laboratory experiments, the first CO2 EOR pilot in the MENA region was conducted as early as 2009 in one of ADNOC Onshore fields. This paved the way for further large-scale deployment and CO2 WAG pilots starting in 2016, both onshore. Appreciable progresses have been made since 2009. This bodes well with the significant initiatives undertaken by the UAE towards carbon emissions and greenhouse gas reduction, climate control and sustainable development. There are broad consensus that climate changes are now and will continue to affect all countries on all continents. Potential global warming can disrupt national economies and adversely impact on lives, costing people, communities and countries already today and perhaps more in the future. Carbon Capture, Utilization, and Storage (CCUS) technologies have been making headlines and attracting increasing amount of renewed attention, because they are in line with meeting global greenhouse gas reduction goals, and contributing towards climate control and sustainable development. The giant Abu Dhabi onshore field consists of 6 carbonate reservoirs. Several pilots, immiscible hydrocarbon gas injection and CO2 WAG, and a pattern immiscible gas injection WAG flood have been executed. Miscible gas injection EOR is therefore field proven. However, due to large field size, surface congestion constraints, geological and fluid variations, miscible gas injection EOR development by reservoir individually becomes complex and economically challenging. This paper presents a comprehensive study and recommends an integrated CCUS Hub development approach - enabling field-wide EOR development with several hundred million-barrels of incremental recovery. The study follows a step-by-step systematic method. Existing water flood performances were assessed first. History matched full field simulation then leads to identification of CO2 EOR targets by area/flank for each reservoir. These are referred to as sweet development areas. Available advanced PVT data were analysed and a multi-reservoir single equation of state developed. It has been found that only CO2 is miscible across all six reservoirs, while hydrocarbon gas is also miscible for the deepest two reservoirs. Dedicated fine scale sector models (EOR history matched where applicable) were developed to generate multiple CO2 EOR development scenarios, for example, depending on water flood maturity at the time of CO2 EOR start-up, and potential impact on incremental oil production, incremental oil recovery due to reservoir heterogeneity. First results from sector modelling show that quite a few areas/flanks would be sub-economical if CO2 EOR development on a stand-alone basis. Hence the concept of a CCUS Hub is proposed, which would allow sweet development areas in any or all of the six reservoirs to be developed from a single common surface Cluster. There is potential space for development phasing, allowing additional CO2 EOR developments within the same cluster area once ullage and CO2 supply becomes available. The CCUS Hub development approach facilitates optimization and sharing of injection/production flow-lines; surface space, gathering and processing facilities, CO2 supply, CO2 recovery unit deployment coupled with produced gas re-injection into the 2 deepest reservoirs. Compared to a more conventional development approach of reservoir by reservoir, considerable scope for CAPEX and OPEX savings was found. Assuming a constant future oil price, a reduction in development costs would allow more sweet development areas to pass the threshold of economical development, leading to an increase in overall incremental production and recovery from CO2 EOR.

Commercialization of Al Reyadah – World's 1st Carbon Capture CCUS Project from Iron & Steel Industry for Enhanced Oil Recovery CO2-EOR

As fossil fuels will continue to be a key source of energy for the world, the role of carbon capture utilization and storage (CCUS) has become increasingly important in addressing climate change by limiting emissions and by establishing a pathway to reaching net-zero. In spite of its significance, the deployment of CCUS globally in the past decade has not met expectations. It is largely due to the challenges in commercializing the technology. On the contrary, ADNOC successfully deployed CCUS in 2016 and has been operating Al Reyadah - the world's first CCUS project in Iron & Steel Industry and Middle East's first commercial CCUS project for enhanced oil recovery (CO2-EOR). Similar to other industrialized economies, Abu Dhabi has various sources where carbon dioxide (CO2) is emitted. It also has an advanced oil & gas industry which requires CO2 for enhanced oil recovery (EOR) in order to improve production output. ADNOC synergized these two industries to create a business case. The concept of a CO2 network, linking CO2 producer (source) and CO2 user for EOR (sinks) was developed as far back as 2008. Various studies where undertaken and a steel facility was identified as an ideal choice for a 1st project, given availability of CO2 and proximity to the ADNOC oil fields. In 2012, Al Reyadah was formed to develop the facility and pipeline that is operating today. This is the first step in a vision that would see multiple sources within Abu Dhabi that will be connected via a pipeline network to supply the CO2 needs of ADNOC for EOR, sequestering CO2 and reducing the UAEs greenhouse footprint, whilst freeing up vital hydrocarbon gases (used currently in EOR) for use in commercial industry. From inception, Al Reyadah has been referenced for decarbonization by many global organizations including International Energy Agency (IEA) and International Renewable Energy Agency (IRENA) and has won prestigious recognitions from Carbon Sequestration Leadership Forum (CSLF) and Emirates Energy Awards (EEA). This paper discusses the various strategies and commercialization tactics that ADNOC applied to deploy this unique project, which is only among 21 CCS/CCUS projects operating in the world in 2020 and a precursor to thousands of CCS/CCUS projects that are expected to be built globally in the coming years.

Application of Full Waveform Inversion to Time-Lapse Walkaway Vertical Seismic Profile Data for CO2-EOR Monitoring in Abu Dhabi: A Feasibility Study on Field and Synthetic Data

This study aims to investigate the feasibility of CO2-EOR monitoring by full waveform inversion (FWI) of time-lapse VSP data in an onshore CO2-EOR site in Abu Dhabi. CO2-EOR monitoring using conventional time-lapse surface seismic in onshore oil fields in Abu Dhabi is often technically challenging for two main reasons. The first is that elastic property change in response to pore fluid substitution is relatively small because the elastic modulus of the reservoir rock frame is far larger than that of the pore fluids. The second is the low repeatability of time-lapse survey data due to high amplitude surface-related noise which varies temporally. However, seismic monitoring with FWI of time-lapse borehole seismic data may offer a solution for these issues. FWI is capable of detecting small velocity changes such as those associated with pore fluid substitution. Furthermore, borehole seismic surveys may provide more highly repeatable, higher quality data compared to surface seismic surveys because borehole seismic data is less affected by surface-related noise. This study consists of two parts, a field data analysis and a synthetic study. In the field data analysis, we studied the resolution and repeatability of FWI results at field-data quality, including the presence of actual noise using time-lapse VSP data. VSP data was acquired at the very early stage of EOR and there was no CO2 injection in the time between the two time-lapse VSP surveys. As a result, a high-resolution P-wave velocity model, consistent with a sonic log, was obtained. The P-wave velocity model also revealed excellent repeatability between the two survey data sets. In the synthetic study, time-lapse FWI was performed using synthetic VSP data representing pre- and post- CO2 injection periods. The results of the synthetic study showed that even in the presence of realistic 4D noise, which was estimated in the field data analysis, FWI successfully delineated the distribution of velocity changes caused by CO2 injection when the cross-sectional area of the injection-induced velocity changes were larger than the resolution of the FWI results. With these results, we demonstrated that FWI using time-lapse VSP data was applicable for CO2-EOR monitoring in the field as long as the criteria were met. This conclusion encourages the application of FWI using time-lapse VSP data for CO2-EOR monitoring in onshore Abu Dhabi.

Fast Optimization of Injector Selection for Waterflood, CO2-EOR and Storage Using an Innovative Machine Learning Framework

Optimal injector selection is a key oilfield development endeavor that can be computationally costly. Methods proposed in the literature to reduce the number of function evaluations are often designed for pattern level analysis and do not scale easily to full field analysis. These methods are rarely applied to both water and miscible gas floods with carbon storage objectives; reservoir management decision making under geological uncertainty is also relatively underexplored. In this work, several innovations are proposed to efficiently determine the optimal injector location under geological uncertainty. A geomodel ensemble is prepared in order to capture the range of geological uncertainty. In these models, the reservoir is divided into multiple well regions that are delineated through spatial clustering. Streamline simulation results are used to train a meta-learner proxy. A posterior sampling algorithm evaluates injector locations across multiple geological realizations. The proposed methodology was applied to a producing field in Asia. The proxy predicted optimal injector locations for water and CO2 EOR and storage floods within several seconds (94–98% R2 scores). Blind tests with geomodels not used in training yielded accuracies greater than 90% (R2 scores). Posterior sampling selected optimal injection locations within minutes compared to hours using numerical simulation. This methodology enabled the rapid evaluation of injector well location for a variety of flood projects. This will aid reservoir managers to rapidly make field development decisions for field scale injection and storage projects under geological uncertainty.