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A one‐dimensional model of fluid pressure and porosity evolution is used to investigate the physical processes that control the development and maintenance of overpressure in a compacting sedimentary basin. We show that for shale‐dominated sequences the variation of the hydraulic diffusivity in both space and time is such that it produces a minimum between 2 and 4 km depth, consistent with observations from the Gulf Coast basin. This minimum inhibits the upward flow of fluid by acting as a “bottleneck” and thus determines the shallowest position of the depth to the top of overpressure. Above this region of bottleneck, overpressure does not develop because the porosity is sufficiently large to maintain high values of hydraulic diffusivity that are conducive to the rapid dissipation of excess fluid pressure. Within the overpressured shales, compaction propagates downward through the section, releasing fluids from the upper part of the section while continuing to restrain the upward flow of fluids from deeper within the section. As such, overpressures are predicted to be maintained within the deeper regions of a basin for tens to hundreds of millions of years. Further, fluid viscosity plays an important role in defining the depth behavior of hydraulic diffusivity as a function of time. Assuming a temperature‐dependent fluid viscosity guarantees that the hydraulic diffusivity minimum will always exist during the development of the basin. On the basis of our results, we find that the depth at which the porosity equals 14±4% correlates with the depth to the local hydraulic diffusivity minimum and thus the depth to the top of overpressure. Moreover, we interpret that the 14±4% represents the threshold porosity for which a shale actually begins to act as a seal. Within the Gulf Coast basin, the gross sediment facies consists of lower massive shales across which deltaic systems have prograded allowing the deposition of an alternating series of sandstones and shales that grade vertically into massive sandstones. The massive sandstones are highly permeable and are connected hydrologically to the surface. We conclude that these sandstones play little role in the development of overpressure because of their high permeability except to the extent that the base of the massive sandstones marks the minimum depth possible for the top of overpressure. In contrast, overpressuring is observed to develop within either the shale‐dominated sequence or the region of interspersed/interfingering sands and clays. The clay‐encompassed sands play only a passive role in the development and maintenance of overpressure because it is the low‐permeability clays that control the movement of fluids into and out of the sands.

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Decision making under uncertainty can be quite challenging, especially when complex numerical simulations are considered in the work flow and the decision has to be made relatively fast (e.g., in hours). This is the case when one needs to rank a given field portfolio within a limited budget and with acquisition constraints. If the ranking measure associated with each field is properly and rapidly evaluated, new prospect opportunities, which may lead to a favorable strategic position, can be readily identified.In this paper, we propose an efficient methodology for computing a "production-potential" measure that can be used to rank greenfield portfolios in the presence of geological uncertainty, quantifying both uncertainty and risk propagation. Next, we briefly describe the basics of the method proposed. First, uncertainty in sedimentary variability and flow behavior has to be characterized by a number of representative geological realizations. Sampling techniques are used to significantly reduce the number of realizations while preserving accuracy in the description and uncertainty propagation. Thereafter, multiple and varied field-development plans, based on primary/secondary-recovery mechanisms, are automatically generated while accounting for key parameters related to the number, drilling locations, and drilling sequence of wells. In these plans the reservoir is clustered by areas with similar production/injection potential, and the well locations and drilling schedules are obtained accordingly. The well controls are determined through estimations of the fieldrecovery factor. By means of experimental-design techniques a relatively small number of field-development plans are selected to capture the most significant production profiles. Each of these development plans is simulated for the realizations sampled previously, and the production-potential measure [e.g., average net present value (NPV) over all sampled realizations] is computed for all the plans. The highest of these measures (i.e., the best development plan) can be used for ranking the greenfield in the portfolio. Response-surface procedures are considered to perform additional analysis computations within iterative optimization procedures. It is important to note that other statistics related to the exploitation potential (e.g., standard deviation of the NPV) can also be used to complement the ranking, thereby mitigating the decision makers' risk tolerance. The methodology has been tested on the Brugge Field benchmark, which presents 104 realizations of multiple geological parameters. The benchmark has been modified to simulate a greenfield scenario. The ranking measure is the (discounted) NPV averaged over the 104 realizations. The proposed work flow yields a ranking measure of USD 5.43 billion, and the computational cost is approximately 1,900 simulations (performed in a parallel-computing environment). This NPV is somewhat higher than those found for the Brugge benchmark (with similar modified settings) by other researchers. To validate the result...