Acidizing Process in Acid Fracturing

The theory and numerical implementation of acid-fracturing model that solves the 2D fracture geometry leakoff, acid transport and acid-rock reaction simultaneously will be presented. The mathematical model proovides a penetration distance for acid fracturing. Due to limitation of analytical solution, a finite-difference method was developed for modelling the fracture acidizing process. Example was solved for HCl reaction in limestone and dolomite fractures, and the results are presented in graphical form. The acid-transport model integrates a number of features which were not accounted for an earlier design models: comprehensive study of hydrodynamic process; acidizing controlled by mass transfer, rate of reaction, and leakoff. Coupling with reservoir forecasting models gives the ability to optimize the job

Numerical Validation of Chemical Compositional Model for Wettability Alteration Processes

Chemical compositional simulation of enhanced oil recovery and surfactant enhanced aquifer remediation processes is a complex task that involves solving dozens of equations for all grid blocks representing a reservoir. In the present work, we perform a numerical validation of the newly developed mathematical formulation which satisfies the conservation laws of mass and energy and allows applying a sequential solution approach to solve the governing equations separately and implicitly. Through its application to the numerical experiment using a wettability alteration model and comparisons with existing chemical compositional model's numerical results, the new model has proven to be practical, reliable and stable

Simulation of mass-transfer process in porous media with complex shape : [abstract]

Some rare minerals and metals are extracted by underground leaching. Thus sorption extraction of minerals on mass-transfer devices with use ion-exchange resin is the most widespread method of productive solutions processing. Now wide application finds sorbing device which represents the cylindrical column, filled by a layer of ion-exchange resin in the form of spherical porous granules. Through a column from below upwards with the filtration velocity the solution containing sorbing a mineral is pumped over. Velocity of solution admission is calculated off on kinetic parameters. A cone barrier located before a submitting pipe is intended for achievement of uniform distribution of a solution across a column [fig.]. On an output from a column through certain time tests of a solution which are analyzed on the maintenance in them of mineral are selected. Sorption proceeds until concentration of mineral on an outlet from a column will not be equal some admissible value. After that the saturated layer of a sorbent being below by a mineral is unloaded. Sorbing device from above is supplemented with a fresh sorbent and process repeats. There are some questions, a degree of an involvement of a sorbent in mass-transfer process (especially, in a transverse direction of a column) and change of column resistance depending on the size and forms of cone barrier, influence of dispersive and kinetic characteristics on thickness of the saturated layer

A COMPARISON OF MACHINE LEARNING ALGORITHMS IN PREDICTING LITHOFACIES: CASE STUDIES FROM NORWAY AND KAZAKHSTAN

Defining distinctive areas of the physical properties of rocks plays an important role in reservoir evaluation and hydrocarbon production as core data are challenging to obtain from all wells. In this work, we study the evaluation of lithofacies values using the machine learning algorithms in the determination of classification from various well log data of Kazakhstan and Norway. We also use the wavelet-transformed data in machine learning algorithms to identify geological properties from the well log data. Numerical results are presented for the multiple oil and gas reservoir data which contain more than 90 released wells from Norway and 10 wells from the Kazakhstan field. We have compared the the machine learning algorithms including KNN, Decision Tree, Random Forest, XGBoost, and LightGBM. The evaluation of the model score is conducted by using metrics such as accuracy, Hamming loss, and penalty matrix. In addition, the influence of the dataset features on the prediction is investigated using the machine learning algorithms. The result of research shows that the Random Forest model has the best score among considered algorithms. In addition, the results are consistent with outcome of the SHapley Additive exPlanations (SHAP) framework

Numerical modeling of the effects of disproportionate permeability reduction water-shutoff treatments on water coning.(Report)(Author abstract)

International audienceIn the present paper, we analyze numerically the disproportionate permeability reduction (DPR) water-shutoff (WSO) treatments in oil production well, i.e., the ability to reduce relative permeability (RP) to water more than to oil. The technique consists of bullhead injection of polymer solutions (gelant) into the near-wellbore formation without zone isolation. By assuming the low dissolution of polymer in oil and the low mobility of the gel in porous medium, we reduced the compositional model of the process to a simple two-phase model, with RP and capillary pressure (PC) dependent on the water and gel saturation. We proposed the extension of the LET correlations used to calculate RP and PC for the case of three phases (oil-water-gel). The problem is divided into two stages: the polymer injection and the post-treatment production. Both of these processes are described by the same formal mathematical model, which results from incompressible two-phase flow equations formulated in terms of normalized saturation and global pressure. The thermal effects caused by the injection of a relatively cold aqueous solution are taken into account. The numerical solution shows favorable results for the DPR WSO treatments. Other techniques, such as the creation of impermeable barrier and downhole water sink (DWS) technology, are also tested in order to check the validity of the developed numerical model with experimental dat

Surgical aspects of obtaining a right liver lobe graft from a live related donor

Seven years' experience in obtaining hepatic fragments from 104 live related donors (RD) is pooled to perform orthotopic transplantations in patients with terminal stages of chronic and diffuse diseases of the liver. The main principles in the selection of RD are outlined. Surgical techniques and a spectrum of postoperative complications, such as bleeding [n = 1 (0.95%)], herniation [n = 1 (0.95%)], and bile leakage [n = 3 (2.85%)], are described. All RDs operated on were sociomedically rehabilitated entirely