Sulfobetaine polymers for effective permeability into multicellular tumor spheroids (MCTSs)

Multicellular tumor spheroids (MCTSs) are attractive for drug screening before animal tests because they emulate an in vivo microenvironment. The permeability of the MCTSs and tumor tissues by the candidate...

Modeling and Analysis of Diagnostic Fracture Injection Tests DFITs

Diagnostic fracture injection tests (DFIT) are used as an indirect method to determine closure pressure and formation effective permeability in unconventional reservoirs as a first step in formation evaluation. The information obtained from DFIT is particularly useful because it is obtained before any production for a given well is available. In DFIT, a small fracture is created by injecting few barrels of completion fluid until formation breaks down and a fracture is initiated and propagates a short distance into the reservoir. Then, injection is stopped, and the pressure decline (or falloff) is monitored. From this pressure decline, the effective permeability of the formation is estimated by Nolte's G-function, log-log plot, or square root of time analysis. In this research, the viability of the common DFIT analysis techniques was investigated for unconventional reservoirs with and without micro-fractures by using a numerical hydraulic fracturing simulator, CFRAC. The results of numerical simulations were investigated to assess the impact of permeability, residual fracture aperture, and complex fracture networks on conventional DFIT interpretations. For the example considered in this work, the commonly used G-function analysis yielded estimates of permeability over an order of magnitude higher than the simulated matrix permeability. Error in the G-function estimates of permeability were higher for higher matrix permeability and in the existence of a fracture network. On the other hand, straight-line analysis of Ap versus G-time yielded much closer (in the same order of magnitude) estimates of permeability.

Dynamic Modeling of the Gas Discharge of a Mine in the Karaganda Coal Basin Under High Uncertainty Using a Multiple Realization Approach

The current work is intended to show the application of a multiple realization approach to produce a strategic development plan for one of the mines in Karaganda coal basin. The presented workflow suggests using a comprehensive reservoir simulator for a history matching process of a coal pillars on a detailed 3D grid and application of sensitivity and uncertainty analyses to produce probabilistic forecast. The suggested workflow significantly differs from the standard approaches previously implemented in the Karaganda Basin. First, a dynamic model has been constructed based on integrated algorithm of petrophysical interpretation and full cycle of geological modeling. Secondly, for the first time in the region, dynamic modeling has been performed via a combination of history matching to the observed degassing data and multiple realization uncertainty analysis. Thirdly, the described model parameters with defined range of uncertainty has been incorporated into the forecasting of degassing efficiency in the mine using different well completion technology. From the hydrodynamic modeling point of view, the coal seam gas (CSG) reservoir is presented as a dual porosity medium: a coal matrix containing adsorbed gas and a network of natural fractures (cleats), which are initially saturated with water. This approach has allowed the proper description of dynamic processes occurring in CSG reservoirs. The gas production from a coal is subject to gas diffusion in coal micropores, the degree of fracture intensity and fracture permeability. By tuning these parameters within reasonable ranges, we have been able to history match our model to the observed data. Moreover, application of an uncertainty analysis has resulted in a range of output parameters (P10, P50, and P90) that were historically observed. Performed full cycle of CSG dynamic modelling including history matching, sensitivity, and uncertainty analyses has been performed to create a robust model with the predictive power. Based on the obtained results, different optimization technologies have been simulated for fast and efficient degassing through a multiple realization probabilistic approach. The coal reservoir presented in this work is characterized by very low effective permeability and final degassing efficiency depends on well-reservoir contact surface. The decrease of the well spacing led to a proportional increase of gas recovery which is very similar to unconventional reservoirs. Therefore, vertical and horizontal wells with hydraulic fractures have been concluded the most efficient way to develop coal seams with low effective permeability in a secondary medium.

Numerical Analysis of Effective Permeability of Concrete-Like Material With a Random Three-Phase Mesostructure

Interfacial transition zone (ITZ) is an important component of a concrete-like material. Accurately simulating the ITZ's characteristics of the concrete-like materials is a difficult process in numerical simulation. This article proposed a random three-phase mesostructural modeling method using the incorporation of random aggregate generation, Minkowski sum theory, and polygon union techniques. It was found that this method can better simulate the mesostructure and ITZ characteristics of concrete-like materials. By using this method, a random three-phase mesostructural model had been built for conducting a finite element analysis to investigate the effective permeability parameters of concrete. A good agreement between numerical and experimental results indicates the feasibility of this method in the concrete-like material analysis.