Currently, oil deposits in the Lower Jurassic strata of the Serginskoye oil and gas region have been identified in several fields, including the Serginskoye, Alekseyevskoye, Zapadno-Yaganokurt, Bolshoye, Karempostskoye, and Yuzhno-Lykhminskoye fields. Many researchers believe that these Lower Jurassic deposits form an independent oil and gas complex, which in- cludes several distinct sandstone layers. As such, searching for and discovering new fields and deposits within these layers is highly relevant. The Y100 layer is one such object. The goal of this study is to define the distribution area of the Y100 layer in the Serginskoye NGR and to identify potential prospective zones. To accomplish this, we conducted a correlation of the Lower Jurassic deposits, analyzed the accumulation conditions and patterns of reservoir rock distribution, refined mapping techniques for the deposits, and reviewed paleotectonic development along with geologi- cal and geophysical surveys. The main findings of the study include identifying the distribution area, constructing thickness profiles, and pinpointing prospective areas of the Y100 reservoir.

Currently, tools such as density imagers are not fully utilized in geonavigation of wells. The authors of this paper propose that the angles and directions of layering obtained through the structural interpretation of density imager data in horizontal wells can be utilized to identify the boundaries and orientations of sand bodies. The aim of this study is to demonstrate new applica-tions of structural interpretation of the density imager in geonavigation of wells.  

An example from a horizontal well illustrates the potential benefits of combining structural interpretation of density imager data with seismic data analysis. Based on the drilling direction, different sand channels were identified, each characterized by varying angles and directions of layering. The directions derived from the density imager interpretation correspond closely with those obtained from seismic data interpretation.  

Analysis of the structural interpretation of density imager data from 52 horizontal wells in-dicates that layers with high dip angles (greater than 15°) generally exhibit better filtration and reservoir properties.  

Therefore, integrating the structural interpretation of density imager data, seismic data, and boundary mapping during the drilling process can aid in defining the boundaries and orientations of geological formations, ultimately helping to determine the optimal direction for further horizon-tal well drilling.

This paper presents findings on the reservoir water of the Aptian-Albian-Cenomanian water-bearing complexes within the Western Siberian Artesian Basin, based on long-term monitoring conducted at oil and gas fields. The study is relevant due to the limited understanding of current hydrogeochemical conditions in the basin, particularly regarding the variability in groundwater chemical composition observed over the monitoring period. We analyzed a substantial dataset comprised of over 4,700 samples of the reservoir water from the Aptian-Albian-Cenomanian sediments at various monitoring sites. To organize and summarize the gathered data for each field, we calculated the average annual concentrations of each component found in the waters, in addition to their standard deviations over time. We also compared the methodological errors associated with laboratory methods for measuring the major components against the standard deviations in the observed data. Furthermore, we assessed the natural heterogeneity of the chemical composition of groundwater within the Aptian-Albian-Cenomanian water-bearing complexes across the studied fields. The results of our long-term hydrogeochemical monitoring reveal significant variability in components such as calcium, bicarbonate, iodine, and bromine within the groundwater, even among individual fields. This variability is largely attributed to the local heterogeneity of the com-position and properties of the surrounding sediments.

The exploration of zones with abnormally high reservoir pressures in the Yamalo-Nenets and Khanty-Mansi Autonomous Okrugs has become essential due to the development of deep hydrocarbon fields. This has led to various technical challenges during reservoir exposing and testing. Elevated and high reservoir pressures are observed in nearly all hydrocarbon-bearing formations, starting from the cap rock of the Achimov sequence, extending through the Upper and Lower Jurassic deposits, and continuing down the geological section. Understanding elevated and high reservoir pressures, along with the mechanisms of their formation, is vital for enhancing the efficiency of deep drilling operations and preventing well control incidents. To address this, a variety of pressure evaluation methods are employed before, during, and after the drilling process. Geophysical methods used during drilling are particularly important for tackling this task.  

This study investigates the potential for determining reservoir pressure using data from wells drilled in multiple fields.  

It demonstrates how the equivalent depth method can be applied to estimate both reservoir pressure and the pressure anomaly coefficient. The results of the study show that this method provides reliable data when applied to the evaluation and testing of deep reservoirs.

A geographic information system has been developed for planning, monitoring, and analyzing geological exploration activities. This system incorporates an intelligent core for data analysis, calculations, and optimization in the face of information uncertainty. The proposed methodologies and algorithms have been implemented in the Subsurface Resource Management System, which is designed to monitor geological exploration work and the use of subsurface resources. This paper discusses using fuzzy and probabilistic models — a hybrid approach — for assessing the resource base and calculating reserves. We have developed deterministic and fuzzy algorithms for geographic information system calculations to determine the optimal placement of exploration wells. To generate uncertainty maps for reserve estimation, we created an original fuzzy algorithm that surpasses the commonly used Monte Carlo method in terms of capability, accuracy, calculation time, and stability. This approach allows us to represent all imprecisely defined parameters as membership functions and utilize the proposed fuzzy operations to analyze real field data. The fuzzy operations for map generation include fuzzy overlay operations, which can be employed to create maps that illustrate the uncertainty of calculated parameters and reserves. We also provide a comparison with the "traffic light" map-building method.

Achimov sequence is characterized by high heterogeneity and low reservoir properties. Development of Achimov sequence occurs using horizontal wells with multistage hydraulic fracturing. Despite the adoption of advanced technologies, the oil recovery factor in these deposits ranges from 5% to 14%. As part of the article, we studied the localization’s process of residual recoverable oil reserves in low-permeability, macro-heterogeneous sandstones with chaotic layered structures in a late-stage field. We studied belonging of sandstones to the filtration-capacitance matrix of the reservoir and the current state of field development. In addition, we analyzed production well operation. As a result, we found areas with undeveloped reserves for infill drilling on the base of depositional environments and facies. We considered all these factors to adapt a hydrodynamic simulation model of a highly heterogeneous reservoir. We utilized this model to select the design system that is optimal in terms of technical and economic indicators.

This article presents an approach for determining the optimal parameters of a reservoir development system, based on a series of multivariate hydrodynamic simulations aimed at model adaptation and forecasting of technological indicators, incorporating neural network analysis. The rationale behind this algorithm is to enhance the accuracy and reliability of results during the early stages of design by simultaneously accounting for geological and hydrodynamic uncertain-ties. The software "tNavigator" was selected as the primary tool due to its extensive feature set tailored for this task. Using the Latin Hypercube algorithm, we conducted a multivariate adaptation of the initial hydrodynamic model. By analyzing the quality of the resulting model, we selected representative implementations for the baseline forecast. Based on the outcomes of baseline forecast and using the accumulated distribution function, we identified pessimistic, baseline, and optimistic scenarios for optimization calculations. These calculations were aimed at finding the most effective development system using the differential evolution algorithm.  

To ensure quality control and refine the optimal parameters obtained, we constructed a neural proxy model. According to the results of the study, we developed a procedure for obtaining desired estimates, which combines a wide range of uncertainties that define the variety of obtained solutions while also reducing the computational time required for simulations.

A wide range of wave and vibration methods are employed to restore the productivity of oil wells, aimed at increasing the permeability of the near-wellbore zone. A necessary step in these technologies is the removal of contaminating particles from the near-wellbore zone, with its sub-sequent transportation to the surface. However, action of wave fields can extend to greater depth. In addition, it can be effectively utilized to clean large areas of the reservoir. The aim of the study is to theoretically justify the process of altering the concentration of colmatant structures in the near-wellbore zone and within hydraulic fracturing (HF) fractures, without necessitating the ex-traction of broken colmatant particles to the surface. When wave fields generated within the well are applied, particles are moving deeper into the reservoir and dispersed over a wider clean area. The theoretical justification was conducted by the method of mathematical modeling. In the course of work, the task of reducing the concentration of contaminant particles in the studied area is formulated and solved, formulas for the change in the amount of sediment and absolute permeability are derived, calculations are made, and graphs are constructed. The results of this study can be applied to the development of a new vibro-wave technology aimed at improving well productivity.

This paper tackles the problem of determining the load-bearing capacity of the wall of a vertical steel cylindrical tank in the presence of shape defects. The aim of this study is to present a methodology for calculating the strength and stability of the tank wall, making it accessible to a broad audience of specialists. The novel approach combines a standard analytical method, as outlined in source, with a numerical method.  

This study utilizes classical methods of structural mechanics, existing analytical solutions, and numerical techniques, specifically the finite element method implemented in the ANSYS software package. The results demonstrate that the proposed combined methodology, which integrates both analytical and numerical methods, effectively addresses the issue of verifying the load-bearing capacity for both newly constructed and existing tanks.  

The approach presented in this article could serve to enhance current regulatory documentation concerning the evaluation of stress-strain states and technical conditions when geometric shape defects are present.

The oil heating furnace is a crucial component of the oil treatment unit and can utilize associated petroleum gas as fuel. However, gases of varying compositions require different amounts of air for complete combustion.  

The required air volume and the heat of combustion can vary significantly depending on the chemical composition of the gas. Currently, the furnace control is carried out using a PID controller to maintain a target outlet temperature for the product. The fuel gas pressure in the supply line is kept constant, and the amount of air is set using pre-calculated coefficients, which are occsionally adjusted based on oxygen measurements in the flue gases. In practice, the air-to-gas ratio is often manually adjusted based on the flame color, while the automatic air pressure control sys-tem is either not utilized or operates inefficiently. PID coefficient settings is infrequently per-formed, leading to inefficient combustion, particularly when burning richer associated petroleum gas. This results in the release of unburned fuel components into the atmosphere and can cause overheating of the oil product.  

In this study, the authors propose furnace control algorithm based on dynamic calculations of heat and mass balances. The primary goals of this algorithm are to maintain the desired outlet temperature of the oil and to ensure the efficient combustion of associated petroleum gas.