Amin Ettehadtavakkol

Measurement of Shale Matrix Permeability and Adsorption with Canister Desorption Test

Permeability estimation is a crucial part of the shale mudrock characterization because it affects the production rate, the pace of recovery and the technically recoverable hydrocarbons. Shale permeability typically falls in the low range of tens of micro-Darcy down to nano-Darcy. Accurate measurement of permeability is a challenging task because the measurement errors are more likely to occur in the low permeability range. This paper presents a common and accurate experimental method for permeability measurement of shale mudrocks known as the canister desorption test. We describe the experiment procedure and present the governing partial differential equation (PDE). The impact of linear and nonlinear adsorption isotherms and the corresponding analytical and numerical solutions are discussed. A workflow for the estimation of permeability and the gas adsorption parameter is presented. The workflow is used to measure the shale matrix permeability and the adsorption parameter for an organic-rich sample from the Marcellus formation. The measurements are in good agreement with an independent study on the Marcellus organic-rich core samples. The results show that the measurement of the adsorption parameter is as important as the permeability measurement in the organic-rich shales. In addition, given that the measurements of permeability and adsorption parameter are performed at a small scale and the gas properties are approximated by average values, it is recommended to perform multiple experiments at different pressures to constrain the uncertainty of the permeability and adsorption measurements. The limitations of the proposed workflow are discussed.

Storage of CO2 in depleted/producing oil reservoirs

This chapter presents a framework for an environmental based assessment of CO2 storage operations in depleted/producing oil reservoirs. We specially focus on the CO2 enhanced oil recovery (EOR) and storage as the primal advantage of the storage in producing and depleted oilfields. We begin with a qualitative assessment of the physical aspects of EOR-storage process. Then we present a basic quantitative method for the EOR-storage performance evaluation. Finally, we discuss the field scale development of EOR operation for industrial CO2 storage and address the environmental assessment of the EOR-storage operation. The contents of this chapter aim to benefit reservoir engineers and geologists who seek to upscale and communicate the technical knowledge on field-scale CO2-EOR operations into tangible environmental and technical performance measures that are better observed by managers and policy makers.

Application of capacitance resistance models to determining interwell connectivity of large-scale mature oil fields

In view of the problems existing in the application of Capacitance Resistance Models (CRMs) to large-scale mature oil fields, Capacitance Resistance Model for Producers (CRMP) was selected for analysis, a simplified procedure for applying CRMP to large-scale mature oil fields was proposed, and some examples were analyzed. Several strategies were presented to optimize the solution method, in order to shorten the solution time and speed up convergence rate. These include the implementation of a global optimization algorithm, parameter scaling, and analytical development of gradient vector and Hessian matrix of the CRMP objective function. These improvements enable the application of CRMP to large-scale problems. Stepwise history matching was shown to be an effective technique to improve reliability of the analysis. Our analysis shows that, the connectivity obtained by the presented method agrees with the interpreted connectivities from the observed CO2 injection and production signals, which proves the reliability of the presented method. The connectivity of an injector to the nearby producers can be analyzed based on the CRMP results, and the analysis can be used for related studies, such as determining current water injectors suited for CO2 injection, or current CO2 injectors not suited for CO2 injection.

Development Optimization and Uncertainty Analysis Methods for Oil and Gas Reservoirs

Uncertainty complicates the development optimization of oil and gas exploration and production projects, but methods have been devised to analyze uncertainty and its impact on optimal decision-making. This paper compares two methods for development optimization and uncertainty analysis: Monte Carlo (MC) simulation and stochastic programming. Two example problems for a gas field development and an oilfield development are solved and discussed to elaborate the advantages and disadvantages of each method. Development optimization involves decisions regarding the configuration of initial capital investment and subsequent operational decisions. Uncertainty analysis involves the quantification of the impact of uncertain parameters on the optimum design concept. The gas field development problem is designed to highlight the differences in the implementation of the two methods and to show that both methods yield the exact same optimum design. The results show that both MC optimization and stochastic programming provide unique benefits, and that the choice of method depends on the goal of the analysis. While the MC method generates more useful information, along with the optimum design configuration, the stochastic programming method is more computationally efficient in determining the optimal solution. Reservoirs comprise multiple compartments and layers with multiphase flow of oil, water, and gas. We present a workflow for development optimization under uncertainty for these reservoirs, and solve an example on the design optimization of a multicompartment, multilayer oilfield development.