Abstract As part of ADNOC's strategic priorities and the Upstream 2.0 initiative, accelerating the development of undeveloped reservoirs is essential to future-proof the business and respond to evolving global energy demands. In this context, there was a recognized necessity to pursue new hydrocarbon opportunities within our offshore fields by leveraging the latest advancements in oil and gas industry technologies—specifically, cutting-edge methods for fluid sampling in tight reservoirs. This approach was complemented by implementing a fast-track modeling workflow, which enabled the rapid evaluation of potential hydrocarbon volumes in place. Alongside this, robust uncertainty analysis was conducted to help inform decision-making and optimize asset development strategies. Acquiring representative fluid samples from tight and challenging reservoir environments has long posed significant technical difficulties due to their low permeability and complex rock properties. To overcome these challenges, advanced reservoir penetration techniques and the deployment of industry-leading sampling tools were employed. These specialized devices allowed for successful extraction of fluid samples in conditions that would traditionally impede accurate data collection, ensuring the integrity and reliability of the samples gathered. This process plays a pivotal role in the precise evaluation of the reservoir, facilitating accurate identification of hydrocarbon potential and enabling informed field development planning. Upon completion of the well interventions and data acquisition campaigns, a rapid two-dimensional analysis was performed, focusing on the lateral variation of reservoir properties and the estimation of possible Free Water Levels (FWL) across multiple wells. This information served as the foundation for the construction of a fast-track static reservoir model. Within this model, Oil-Water Contacts (OWC) and various reservoir rock typing scenarios were postulated, which were subsequently incorporated into a comprehensive sensitivity analysis to estimate a range of Oil Initially In Place (OIIP) volumes. One of the significant achievements of this project was the first-time deployment of state-of-the-art technology for pressure and reservoir fluid sampling using a multi-probe system with an exceptionally large area packer. Unlike conventional methods that often necessitate the use of inflatable packers in low-mobility formations, this innovative tool enabled efficient testing and sampling without additional equipment, ultimately streamlining operations and reducing risk. The successful application of this advanced technology not only provided high-quality fluid samples from a previously unsampled tight reservoir but also set a new benchmark for future reservoir evaluation efforts. Following the successful data acquisition phase, two-dimensional maps displaying porosity, permeability, and net pay thickness were generated using input from all available well data. These visualizations enhanced the understanding of reservoir trends and heterogeneities. Further, several rock typing methodologies, including the Winland and Lucia models, were evaluated to assign reservoir rock types and assess their impact on volumetric estimations. Minimum, mid, and maximum Free Water Level (FWL) values were derived from well logs in the newly appraised reservoir, feeding into sensitivity analyses to better understand their influence on volumetric calculations and resource estimates. This abstract highlights the practical application of a breakthrough fluid sampling tool enabling the acquisition of representative fluid samples from tight reservoirs for the first time. It also demonstrates the value of integrating fast-track data analysis and modeling within a comprehensive workflow to improve understanding of reservoir characteristics, Free Water Level variations, and their collective impact on volumetric assessment. The lessons learned and methods developed through this work pave the way for more effective reservoir evaluation and optimized resource development in challenging environments, supporting ADNOC's continued commitment to innovation and operational excellence.
Ibrahim et al. (Mon,) studied this question.