Geopressure estimation is an important aspect of well planning and execution. However, there are many sources of uncertainty that can affect the accuracy and timing of the prognosis. These uncertainties are associated with data produced by many different disciplines at various times throughout the life of the well. As subject matter experts tend to work in silos these uncertainties are often unshared, and there is no appropriate routine performance of uncertainty propagation across disciplines. This can negatively affect decision making during both the engineering and operational phases of a well. Uncertainty requirements across disciplines are often not formulated into coherent uncertainty management. It is therefore important to understand the possible sources of uncertainty to better quantify the estimation of geopressures and to make smarter decisions.
This paper describes the uncertainties associated with each estimate of geopressure, their locations in the multi-discipline silos, and the current relationship between estimates. With this comes the realization of a structure or method for combining the individual uncertainties to provide a clearer idea of geopressure estimation and its inherent uncertainty. For instance, combining wellbore position uncertainty with the stratigraphic earth model uncertainty makes possible the estimation of the spatial probability distribution of particular geopressure related observations.
The sources of information for geopressure prognosis are many, spread across disparate systems with various discipline ownership. Even direct and real-time observations of formation fluid influx, borehole collapse or formation fracturing can depend on the precision of downhole pressure measurements and knowledge. Extrapolate measured downhole pressures to positions far removed from the measurement point is often necessary. This requires accurate calculation of hydrostatic and hydrodynamic pressures and the wellbore and vertical depth positions to infer pressure profiles along the borehole. These profiles are a function of the accuracy of characterization of the pressure and temperature behavior of the drilling fluid properties and the well depth. Temperature estimations depend on definition of geothermal gradients and the precision of heat transfer calculations causing a varying degree of accuracy for baseline profiles to base operational decision.
It is possible to measure pore pressures in situ, or to estimate them using trend analysis of formation evaluation or drilling logs. Factors influencing the precision of the results include the actual measurement depth value uncertainty, and the impact of wellbore position uncertainty on their correlation with an earth model. Leak-off tests deliver information about geopressure margins, but the interpretation of flow-back measurements creates further uncertainties that propagate across the prognosis.
The propagated uncertainties from all these sources can be derived using stochastic simulations, yielding, when combined, a quantitative assessment of geopressures. In addition, Kriging methods can incorporate new geopressure estimations in a geomechanics oriented earth model.
The paper provides a list of possible sources of uncertainties and a possible categorization of their origins. It describes the causal links between the sources of uncertainties and their effect on the quality of geopressure prognosis. The purpose is to facilitate the adoption of quantitative uncertainty assessment methods by the well construction community for geopressure estimations.
