The concept of minimum economic field size (MEFS) has been used by explorationists for almost four decades. MEFS is often the only filter to distinguish between a commercial and a non-commercial discovery—far before a wildcat well is drilled—to test a prospect for a working petroleum systems hypothesis. As simple as it gets, the concept started to lose traction in the 21st century as subsurface targets became more and more challenging. In the case of tight hydrocarbons, it is fairly common to observe a P90 case net present value (NPV) to be negative, a P50 case to be positive, and a P10 case to be negative again. The reason for this outcome is that a whole set of full-cycle factors, in addition to the field size, affects prospect commerciality. Their uncertainty ranges can match or exceed resource estimate uncertainty. These factors include, but are not limited to, initial productivity of development wells, estimated eltimate recovery (EUR) per well, decline curve parameters, capital investments, operating costs, and the project phases’ durations. A new way of handling the full universe of risks and uncertainties faced by modern explorers is already available in the new generation of industry-leading integrated prospect risk, resource and value assessment software. Innovators and thought leaders can already substitute MEFS with a commerciality threshold (CT) that neatly mimics board considerations at the final investment decision (FID) stage gate. Others can consider the economic chance of success (ECOS) estimated with a probabilistic full-cycle mindset, as an additional metric valuable for risk management purposes. Using fictional case studies inspired by real-life assessment situations, we discuss the additional value creation by a CT-powered workflow as compared to an MEFS-based one and explain the reasons for the key differences. The discussed workflow does not eliminate nature-specific uncertainties; neither does it reduce the geological risk. However, it helps to better understand human-controlled risks and prepare management exploration decisions with a greater degree of confidence.

Mesozoic age Golapalli sands are found in the Krishna Godavari Basin, located in the East coast of India. These sands are highly prospective for hydrocarbon exploration and development. They comprise of syn rift sediments, often, exhibiting low permeability. In general, these reservoirs do not flow naturally without hydraulic fracturing. Oil presence in Golapalli sands has already been proven in the basin from the exploratory wells. However, conventional saturation modeling using basic petrophysical logs has proved futile in establishing a definite oil water contact (OWC). This adds further complexity in the reserve evaluation and the hydraulic fracturing design. Moreover, the field is divided into multiple fault blocks with localized OWCs. During the initial appraisal phase, wells that were hydraulically fractured produced oil with high water cut. This prompted re-evaluation of saturation modelling with 3 further appraisal wells. All new wells were selected at different fault blocks within the field and were to be drilled as slim holes of 5-7/8in diameter in reservoir section. Potential intervals with natural fractures were successfully evaluated using advanced sonic data. Zones of interest were selected integrating the fractures network identified with advance sonic measurements and high porosity values obtained from basic neutron-density logs. To constrain inversion resistivity-based saturation modelling, a new workflow was adopted to determine reservoir fluid movements prior to hydraulic fracturing in less than 0.05mD formation. Through this approach, fluid saturations were successfully evaluated using a deterministic downhole fluid identification which helped in reducing saturation uncertainties while demarking the transition zone between oil and water in 0.05mD formation. With known oil zone identified, advanced sonic measurements were used to design effective hydraulic fracture models. A successful hydraulic fracture was initiated with excellent oil production with significantly reduced water cut compared to previous wells. In this paper, a novel workflow will be presented that will help in characterizing fluids in tight sands (permeability less than 0.05mD). This workflow integrates the basic openhole logs and formation testing with conventional resistivity-based saturation modeling to accurately pinpoint the OWC in the tight sands. This workflow has applicability in unconventionally tight reservoirs where there is uncertainty in fluid saturations or fluid contacts. Through this methodology, the propagation of hydraulic fracture into the water zone can be prevented which will greatly help in reducing the water cut in such conditions.