The depletion of conventional oil reserves creates a significant demand for the development and improvement of methods and technologies for the production of hard-to-recover oil. A huge potential for hard-to-recover oil in Western Siberia lies in the Pokur suite (PK). These deposits are characterized by high oil viscosity and, accordingly, early water breakthrough. This study identifies and substantiates an effective technology for oil production from such and similar deposits using polymer flooding. The obtained data are based on research of the geological structure, the main reservoir properties and those of its fluids, chemical and laboratory methods of analysis, and the results of mathematical and hydrodynamic modeling. According to the results of hydrodynamic modeling, the greatest technological effect of polymeric water flooding is observed in the model of collector permeability at 70 mD and above 1000 mD, but this technology is not recommended for reservoirs with an average permeability of less than 10 mD. Implementation of the best practices through the prism of the resource nexus allows sustainable water management by applying environment-friendly polymers for enhanced oil recovery and contributes to the UN Goal 6 of clean water and sanitation.

This article reviews the results of measurement of optical properties of oil, such as polarimetry, refractometric, luminescent-bituminological research, IR-spectrometry and UV-visible-NIR spectrometry used to solve geo-bituminology development of hydrocarbon deposits. The authors pay special attention to optical research in the field of UV-visible-NIR electromagnetic radiation, the results of which allow us to estimate the residual oil reserves, separate production for each formation during the operation of multi-layer objects, determine the producing gas-oil ratio, density and content of hydrocarbons, efficiency of hydraulic fracturing, flow-reducing technologies, and injection of solvents of heavy oil sediments, etc. The published approaches to methods of optical research, which are carried out by laboratories or in-well devices, have been analyzed. This article analyzes the main advantages and disadvantages of current technologies for determining the optical properties of oil. The authors propose wellhead devices for determining the optical properties of oil in UV-visible-NIR radiation (190–1100 nm) and their functional schemes, with a description of the operating principle.

Recently, more and more new oil fields entering commercial production are complicated by the content of high-viscosity products, which are located at relatively shallow depths. For the rational development of such fields, a network of horizontal wells is used. A special feature of these objects is a weakly cemented reservoir, which leads to significant sand occurrence during well operation. At the same time, the removal of mechanical impurities cannot be avoided even when using complex measures, including the use of various filters. There are quite a few methods describing the behavior of mechanical impurities in gas–liquid flows. The purpose of the work was to analyze the removal of mechanical impurity particles from horizontal wells with high-viscosity oil. A model of a typical well in the OLGA software was created, and data on the types of particle removal were obtained. As a result of calculations, the quality of removal for different diameters of mechanical impurities was determined, and the dependence of the critical diameter on the well flow rate was constructed.

In the process of field exploration, along with regular flooding, a significant part of the wells is flooded prematurely due to leakage of the string and outer annulus. In an effort to intensify the flow of oil to the bottom of wells in field conditions, specialists often try to solve this problem by using various technologies that change the reservoir characteristics of the formation. Any increase in pressure that exceeds the strength of the rocks in compression or tension leads to rock deformation (destruction of the cement stone, creation of new cracks). Moreover, repeated operations under pressure, as a rule, lead to an increase in water cut and the appearance of behind-the-casing circulations. For that reason, an important condition for maintaining their efficient operation is the timely forecasting of such negative phenomena as behind-casing cross flow and casing leakage. The purpose of the work is to increase the efficiency of well interventions and workover operations by using machine learning algorithms for predicting well disturbances. Prediction based on machine learning methods, regression analysis, identifying outliers in the data, visualization and interactive processing. The algorithms based on oil wells operation data allow training the forecasting model and, on its basis, determine the presence or absence of disturbances in the wells. As a result, the machine forecast showed high accuracy in identifying wells with disturbances. Based on this, candidate wells can be selected for further work. For each specific well, an optimal set of studies can be planned, as well as candidate wells can be selected for further repair and isolation work. In addition, in the course of this work, a set of scientific and technical solutions was developed using machine learning algorithms. This approach will allow predicting disturbances in the well without stopping it.

This paper presents a device designed to prevent freezing of back pressure valve of the oil well X-mas tree. The work indicated the relevance of the problem, considered the devices used in oil fields and analyzed their shortcomings. The result of the work was an easy-to-use, easy-to-repair and inexpensive device, which is devoid of the shortcomings of the considered models. Analysis and deduction were chosen as the main methods of study. This work contains 8 figures, 2 tables, a bibliographic list of 15 titles.