This paper presents a collaborative study conducted with Rystad Energy to develop probabilistic estimates of key cost, schedule, and performance parameters for the stochastic valuation of a bluefield exploration asset. Using a dataset of 73 shallow offshore fields in Australia, covering reserves, production histories, financial metrics, breakeven prices, ownership details, and other critical indicators, the analysis examines a wide spectrum of development concepts, including steel platforms, concrete gravity based structures, extended reach drilling projects, FPSO solutions, and subsea tiebacks. Together, these assets represent USD 99.1 billion in historical capital expenditure. The study derives probability distributions for full cycle inputs such as facility Capex per unit of peak production, development phase duration, drilling expenditures per BOE, exploration and appraisal well costs, Opex to Capex ratios, abandonment cost ratios, plateau production behavior, remaining reserves at plateau termination, terminal production rates, and the fraction of pre drilled wells. Most parameters exhibit log-normal characteristics, highlighting the skewed and uncertain nature of early-phase development data. By integrating these probabilistic inputs into a risk, resource, and value simulation environment, the work demonstrates a structured, data-driven approach to assessing value, uncertainty, and risk for early-stage exploration prospects. The methodology is broadly transferable and can be adapted to other basins supported by comprehensive analog datasets.