Morteza Akbarabadi

A Bayesian framework for the validation of models for subsurface flows: synthetic experiments

We present a new Bayesian framework for the validation of models for subsurface flows. We use a compositional model to simulate CO2 storage in saline aquifers, comparing simulated saturations to observed saturations, together with a Bayesian analysis, to refine the permeability field. At the laboratory scale, we consider a core that is initially fully saturated with brine in a drainage experiment performed at aquifer conditions. Two types of data are incorporated in the framework: the porosity field in the entire core and CO2 saturation values at equally spaced core slices for several values of time. These parameters are directly measured with a computed tomography scanner. We then find permeability fields that (1) are consistent with the measured parameters and, at the same time, (2) allow one to predict future fluid flow. We combine high performance computing, Bayesian inference, and a Markov chain Monte Carlo (McMC) method for characterizing the posterior distribution of the permeability field conditioned on the available dynamic measurements (saturation values at slices). We assess the quality of our characterization procedure by Monte Carlo predictive simulations, using permeability fields sampled from the posterior distribution. In our characterization step, we solve a compositional two-phase flow model for each permeability proposal and compare the solution of the model with the measured data. To establish the feasibility of the proposed framework, we present computational experiments involving a synthetic permeability field known in detail. The experiments show that the framework captures almost all the information about the heterogeneity of the permeability field of the core. We then apply the framework to real cores, using data measured in the laboratory.

Salt Precipitation in Ultratight Porous Media and Its Impact on Pore Connectivity and Hydraulic Conductivity: SALT PRECIPITATION IN POROUS MEDIA

The degree of salt precipitation and its impact on fluid flow in ultratight porous media are investigated in three preserved core plugs selected from two different wells in an unconventional hydrocarbon reservoir. Small specimens are cut from the core plugs and then imaged using a focused ion beam scanning electron microscope (FIB-SEM) to detect any salt precipitation in the pore space. The SEM results show that salt covers the pore walls and either partially or fully blocks pore elements, making some parts of the pore space inaccessible to flow. To examine the effect of salt removal on fluid flow, one of the core plugs is subjected to a cleaning process. The plug is initially saturated with methanol, and then methanol is continuously injected into the sample while the effluent is periodically titrated using silver nitrate to monitor salt removal. The variation of the salinity of the methanol effluent with time, the decrease in the pressure drop across the core, and the increased permeability to methanol indicated the effectiveness of the cleaning process. The successful removal of salt from the sample prompts the adoption of a new workflow for preparing tight rock samples for laboratory experiments.