BD Cluster green fields development located offshore Sabah, Malaysia, consists of three multi-stacked turbidite fields, namely A, B and C, encompassing thick and thin bed sands. Due to the lack of existing infrastructure in close proximity, a wellhead platform (WHP) will be installed on top of Field A. Fields B and C will be developed with a respective 8 and 7km subsea tie back to this WHP. Gas will be exported from the WHP to Facility-1 situated 5km away, whereas oil from a single thin oil rim reservoir in Field A will be exported to Facility-2 50km away. The challenges faced by the Reservoir Engineering (RE) Team was delivering an extensive number of dynamic simulations while adhering to the Field Development Planning (FDP) submission deadline: 1) uncertainty analysis and probabilistic modelling for 9 models, 2) construction of coupled reservoir models 3) screening alternative oil and gas export routes, and 4) optimizing capex phasing by determining the optimum startup sequence of the fields. Delivering the FDP work on time with the limited software licenses and computing infrastructure available on-premise appeared to be a "bridge too far". The limitations were addressed by PETRONAS LiveFDP digital transformation initiative commenced in 2019, through deployment of digital cloud technologies and solutions with scalable High-Performance Computing (HPC) environment. A total of 9 geological models were delivered to REs for dynamic simulation studies. Probabilistic modelling was then employed to obtain the dynamic P10, P50 and P90 models for each field. The Reservoir Coupling facility and Extended Network option were used in the numerical simulator to couple the standalone models in order to honor the overall facility constraints and incorporate the pipeline effects. Utilizing the coupled network model, multiple studies including condensate banking, determining optimum field sequencing and export route scenario were performed. The FDP subsurface development simulation runs were completed within 1 month using HPC cloud solutions and workflows compared to 9 months if using on-premise infrastructure. It provided the necessary tools to allow the team: 1) accurately assess the impact of condensate banking on well productivity, 2) executed over 1200 cases for probabilistic modelling for the 9 models in 24 hours of simulation time, 3) reduced the number of wells derived from a previous study from 14 to 9 yielding a saving of ~US$115 million, 4) ~US$50 million savings as a result of capex phasing by optimizing the field start up sequence, and 5) US$130 million savings by establishing the lowest cost oil and gas export route scenario.