Characterizing Petrophysical Uncertainties of Thin-Bedded Gas Sands With Cores and Production Data

In this paper, we study the largest producing gas field in SE Asia that supplies about 50% of the domestic gas demand. During the development of the field, production data analysis revealed that conventional sands received pressure support from thin-bedded sands, which were originally considered nonreservoir rocks. Following this analysis, a petrophysical framework was constructed to estimate gas-filled pore volume in the thin-bedded facies (TBF). Subsequent perforations in the TBF and production logs (PLT) confirmed the productivity of these intervals and the validity of the petrophysical model. Although this model delivered several viable scenarios of gas in place, the inherent uncertainty in key petrophysical properties was not addressed. In this paper, we characterize the uncertainties of the volume of shale (Vsh), porosity, facies, and water saturation (Sw) in TBF. The primary guidance we rely on for uncertainty modeling is the dynamic data, such as PLT or shut-in tubing pressure after perforation. Core is also available in the TBF, but most samples contain shale laminations, making core-scale porosity and Sw more pessimistic than reality. The Vsh uncertainty is derived from Monte Carlo simulation, which samples gamma ray endpoints for sand and shale from distributions defined by log data. The 1,000 realizations are produced at each depth, and the P10 and P90 realizations are used as low and high cases, respectively. The mid-case Vsh is taken from a deterministic multimineral model. The uncertainty of sand porosity comes from Monte Carlo simulation of the equation phi_sand=(phi_log- Vsh *phi_shale)/(1 – Vsh), where Vsh and phi_shale are sampled from known distributions derived from log data. The low- and high-case porosity are defined by P10 and P90 of the realizations. The mid-case porosity comes from the deterministic petrophysical analysis. We validate this model in thick sands, where the three cases of porosity collapse into one curve and match core porosity very well. Facies prediction is driven by PLT results at thin-bedded intervals in three wells. We create a mid-case facies model based on neutron-density separation. This model was calibrated with the flow behavior from PLT results. To generate low and high cases, we take the Vsh uncertainty and other conventional wireline logs into an unsupervised clustering, which gives an appropriate range of uncertainties for these petrophysical properties. For mid-case Sw, since the resistivity log always gives a pessimistic result in TBF, we build a saturation height function based on capillary pressure data. The low and high cases are created by observing the spread in capillary curve fits and changing the Thomeer parameters to form the upper and lower bounds around the mid case. The interpreted petrophysical properties and facies, along with their ranges of uncertainties, were used to populate the geological reservoir model, which was simulated and history matched. The results show a good match with the observed pressure and flow rate. The novelty of this paper is that it documents a complete workflow to quantify petrophysical uncertainties in thin laminations (centimeter scale) with only conventional wireline logs, flow tests, and limited cores.