Coupled Effect of Imbibition Capillary Pressure and Matrix-Fracture Transfer on Oil Recovery from Dual-Permeability Reservoirs

This paper presents a numerical study to examine how the interplay between the matrix imbibition capillary pressure (Pci) and matrix-fracture transfer affects oil recovery from naturally-fractured reservoirs under waterflooding. We use a dual-porosity, dual-permeability (DPDP) finite difference simulator to investigate the impact of uncertainties in Pci on the waterflood recovery behavior and matrix-fracture transfer. A comprehensive assessment of the factors that control the matrix-fracture transfer, namely Pci, gravity forces, shape factor and fracture-matrix permeabilities is presented. We examine how the use of Pci curves in reservoir simulation can affect the recovery assessment. We present two conceptual scenarios to demonstrate the impact of spontaneous and forced imbibition on the flood-front movement, waterflood recovery processes, and ultimate recovery in the DPDP reservoir systems of varying reservoir quality. The results demonstrate that the inclusion of Pci in reservoir simulation delays the breakthrough time due to a higher displacement efficiency. The study reveals that the matrix-fracture transfer is mainly controlled by the fracture surface area, fracture permeability, shape factor, and the uncertainty in Pci. We underline a discrepancy among various shape factors proposed in the literature due to three main factors: (1) the variations in matrix-block geometries considered, (2) how the physics of imbibition forces that control the multiphase fluid transfer is captured, and (3) how the assumption of pseudo steady-state flow is addressed.

Matrix Refinement in Mass Transport Across Fracture-Matrix Interface: Application to Improved Oil Recovery in Fractured Reservoirs

In this paper, we will show that it is highly beneficial to model dual-porosity reservoirs using matrix refinement (similar to the multiple interacting continua, MINC, of Preuss, 1985) for water displacing oil. Two practical situations are considered. The first is the effect of matrix refinement on the unsteady-state pressure solution, and the second situation is modeling water-oil, Buckley-Leverett (BL) displacement in waterflooding a fracture-dominated flow domain. The usefulness of matrix refinement will be illustrated using a three-node refinement of individual matrix blocks. Furthermore, this model was modified to account for matrix block size variability within each grid cell (in other words, statistical distribution of matrix size within each grid cell) using a discrete matrix-block-size distribution function. The paper will include two mathematical models, one unsteady-state pressure solution of the pressure diffusivity equation for use in rate transient analysis, and a second model, the Buckley-Leverett model to track saturation changes both in the reservoir fractures and within individual matrix blocks. To illustrate the effect of matrix heterogeneity on modeling results, we used three matrix bock sizes within each computation grid and one level of grid refinement for the individual matrix blocks. A critical issue in dual-porosity modeling is that much of the fluid interactions occur at the fracture-matrix interface. Therefore, refining the matrix block helps capture a more accurate transport of the fluid in-and-out of the matrix blocks. Our numerical results indicate that the none-refined matrix models provide only a poor approximation to saturation distribution within individual matrices. In other words, the saturation distribution is numerically dispersed; that is, no matrix refinement causes unwarranted large numerical dispersion in saturation distribution. Furthermore, matrix block size-distribution is more representative of fractured reservoirs.

On solving classes of positive-definite quantum linear systems with quadratically improved runtime in the condition number

Quantum algorithms for solving the Quantum Linear System (QLS) problem are among the most investigated quantum algorithms of recent times, with potential applications including the solution of computationally intractable differential equations and speed-ups in machine learning. A fundamental parameter governing the efficiency of QLS solvers is κ, the condition number of the coefficient matrix A, as it has been known since the inception of the QLS problem that for worst-case instances the runtime scales at least linearly in κ [Harrow, Hassidim and Lloyd, PRL 103, 150502 (2009)]. However, for the case of positive-definite matrices classical algorithms can solve linear systems with a runtime scaling as κ, a quadratic improvement compared to the the indefinite case. It is then natural to ask whether QLS solvers may hold an analogous improvement. In this work we answer the question in the negative, showing that solving a QLS entails a runtime linear in κ also when A is positive definite. We then identify broad classes of positive-definite QLS where this lower bound can be circumvented and present two new quantum algorithms featuring a quadratic speed-up in κ: the first is based on efficiently implementing a matrix-block-encoding of A−1, the second constructs a decomposition of the form A=LL† to precondition the system. These methods are widely applicable and both allow to efficiently solve BQP-complete problems.

Double matrix completion for circRNA-disease association prediction

Background Circular RNAs (circRNAs) are a class of single-stranded RNA molecules with a closed-loop structure. A growing body of research has shown that circRNAs are closely related to the development of diseases. Because biological experiments to verify circRNA-disease associations are time-consuming and wasteful of resources, it is necessary to propose a reliable computational method to predict the potential candidate circRNA-disease associations for biological experiments to make them more efficient. Results In this paper, we propose a double matrix completion method (DMCCDA) for predicting potential circRNA-disease associations. First, we constructed a similarity matrix of circRNA and disease according to circRNA sequence information and semantic disease information. We also built a Gauss interaction profile similarity matrix for circRNA and disease based on experimentally verified circRNA-disease associations. Then, the corresponding circRNA sequence similarity and semantic similarity of disease are used to update the association matrix from the perspective of circRNA and disease, respectively, by matrix multiplication. Finally, from the perspective of circRNA and disease, matrix completion is used to update the matrix block, which is formed by splicing the association matrix obtained in the previous step with the corresponding Gaussian similarity matrix. Compared with other approaches, the model of DMCCDA has a relatively good result in leave-one-out cross-validation and five-fold cross-validation. Additionally, the results of the case studies illustrate the effectiveness of the DMCCDA model. Conclusion The results show that our method works well for recommending the potential circRNAs for a disease for biological experiments.

Numerical modeling of molecular diffusion and convection effects during gas injection into naturally fractured oil reservoirs

Gas injection into a naturally fractured oil reservoir keeps the reservoir pressure and increments the initial recovery from the reservoir. The main aim of this work was to develop a numerical model to calculate the mass transfer (molecular diffusion and convection) between a gas injected in the fracture and residual fluid (gas and oil) in a matrix block. The dual continuum model is applied to describe flow behaviour and fluid recovery in porous media. Finally, the model is validated by comparing the outcomes with the results of two experimental works available in the literature. The mathematical model results are in agreement with the laboratory data including recovery of each component, saturation profile, and the pressure gradient between matrix and fracture. Modeling results show that after 25 days of N2 injection, the lighter and heavier components (C1 and C5) are recovered about 51% and 39%, respectively. These amounts for CO2 injection are 49% and 27%. It is found that the convection mechanism has a great effect on preventing the pressure drop of the reservoir during injection operations. In the nitrogen injection, without considering the convection, after 30 days, the matrix pressure reaches 1320 Psi from 1479 Psi but after 30 days, considering the convection, the pressure reaches 1473 Psi from 1479 Psi.

MATRIX BLOCK-COMPONENT MODEL OF THE FORMATION OF A CULTURE OF LIFE SAFETY

The construction of a matrix block-component model is considered. The differential and integral indicators of diagnostics of the formation of a culture of life safety are given.

THREE-DIMENSIONAL SIMULATION OF FLUID FLOW THROUGH A DISCRETE FRACTURE AND MATRIX

The study of fluid flow mechanics in fractured porous rocks is crucial in the area of oil and gas production industries, enhanced geothermal system (EGS), CO2 sequestration, disposal of nuclear waste in deep geological repositories (DGR), etc. There are usually two types of flows in fractured rockmass setting. The dominant flow occurs through the fractures whereas there is also a slow movement of fluid through the matrix block. The fluid movement between fracture and matrix is often continuous across the fracture. The present study focuses on the development of a numerical model which can simulate the flow behavior through fracture and matrix simultaneously, which is also known as dual permeability model. To simulate this problem, a 3D model is built in COMSOL Multiphysics 4.3a where a cylindrical geometry is made, and a fracture is defined parallel to the axis of the geometry. The asperity of the fracture is defined by a variable ‘a’ which varies along the x-axis, in such a way that increases the value of ‘a’ alters the geometry of fracture and increases the roughness of fracture. Darcy flow physics is used to simulate the situation with known parameters like porosity, permeability, storage coefficient, etc. Pressure is applied as a boundary condition at two ends of the geometry which acts as driving force for fluid to flow through the block. The influence of fracture asperity on the flow behavior is examined by doing the parametric study and the study shows the decrement in the velocity magnitude with an increase in asperity. The formation of dual flow velocity regime, one along the defined fracture and the other along with the matrix, indicates the efficiency of the developed dual-porosity and permeability model.

ERgene: Python library for screening endogenous reference genes

In gene expression analysis, sample differences and experimental operation differences are common, but sometimes, these differences will cause serious errors to the results or even make the results meaningless. Finding suitable internal reference genes efficiently to eliminate errors is a challenge. Aside from the need for high efficiency, there is no package for screening endogenous genes available in Python. Here, we introduce ERgene, a Python library for screening endogenous reference genes. It has extremely high computational efficiency and simple operation steps. The principle is based on the inverse process of the internal reference method, and the robust matrix block operation makes the selection of internal reference genes faster than any other method.