Sergey Kryuchkov

Thermal Conductivity Measurements of Bitumen Bearing Reservoir Rocks

Summary The increasing imperative to reliably forecast thermal recovery in bituminous reservoirs has heightened interest to study thermal properties of rock-fluid systems, notably that of thermal conductivity. Several measurement techniques have been developed. However, these are typically fraught with limitations aiming at an amenable analytical asssessment. As a result, complex calibrations are implemented, which are susceptible to numerous errors. In this paper, an alternative, more accurate and unique method of thermal conductivity measurement is presented. The method combines two different measurement systems that are capable of measuring heat flux axially and radially. Nonetheless, in both experimental systems, heat is transferred across the test sample after a temperature gradient is established between two defined regions of the sample. The apparati are complemented by computational fluid dynamic models that mimic the physical models at the measurement conditions. A combination of the physical measurements and numerical simulations under steady state conditions is used to provide the final thermal conductivity values. A number of fluid and reservoir samples are tested in order to demonstrate the capabilities of the method. These tests provide evidence of the utility of the method in allowing for variability of sample form, as well as temperature and pressure conditions. Furthermore, both physical experiments and computational models permit and sufficiently account for fluid flow while thermal conductivity is being measured. It is shown that this method is distinctively able to yield accurate results irrespective of the sample size and shape limitations, and attendant heat losses.

Parsimony and goodness-of-fit in multi-dimensional NMR inversion

Multi-dimensional nuclear magnetic resonance (NMR) experiments are often used for study of molecular structure and dynamics of matter in core analysis and reservoir evaluation. Industrial applications of multi-dimensional NMR involve a high-dimensional measurement dataset with complicated correlation structure and require rapid and stable inversion algorithms from the time domain to the relaxation rate and/or diffusion domains. In practice, applying existing inverse algorithms with a large number of parameter values leads to an infinite number of solutions with a reasonable fit to the NMR data. The interpretation of such variability of multiple solutions and selection of the most appropriate solution could be a very complex problem. In most cases the characteristics of materials have sparse signatures, and investigators would like to distinguish the most significant relaxation and diffusion values of the materials. To produce an easy to interpret and unique NMR distribution with the finite number of the principal parameter values, we introduce a new method for NMR inversion. The method is constructed based on the trade-off between the conventional goodness-of-fit approach to multivariate data and the principle of parsimony guaranteeing inversion with the least number of parameter values. We suggest performing the inversion of NMR data using the forward stepwise regression selection algorithm. To account for the trade-off between goodness-of-fit and parsimony, the objective function is selected based on Akaike Information Criterion (AIC). The performance of the developed multi-dimensional NMR inversion method and its comparison with conventional methods are illustrated using real data for samples with bitumen, water and clay.

Advances in multiphase flow measurements using magnetic resonance relaxometry

When it comes to the measurement of bitumen and water content as they are produced from thermally exploited reservoirs (cyclic steam stimulation or steam assisted gravity drainage) most of the current tools that are available in the market fail. This was demonstrated previously when our group introduced the first concept of a magnetic resonance based water-cut meter. The use of magnetic resonance as a potential tool for fluid cut metering from thermally produced heavy oil and bitumen reservoirs is revisited. At first a review of the work to date is presented. Our recent approach in the tackling of this problem follows. A patented process is coupled with a patented pipe design that can be used inside a magnetic field and can capture fluids up to 260°C and 4.2MPa. The paper describes the technical advances to this goal and offers a first glimpse of field data from an actual thermal facility for bitumen production. The paper also addresses an approach for converting the current discrete measurement device into a continuous measurement system. Preliminary results for this new concept are also presented.