The unified system for storing and accessing geophysical data. Traditions and new approaches

The features of the development of data collection systems within the Information Processing Center (IPC) of the Geophysical Survey of the Russian Academy of Sciences (GS RAS) are presenting. Historical information is given, including technical details related to the systematization of the archive and the evolution of geophysical data formats. The historical, territorial features, as well as the experience of deploying such information systems within the Federal Research Center of the Unified State Social Service of the Russian Academy of Sciences and abroad are taken into account. A new concept of building an information system is proposed, which takes into account the requirements for scalability, reproducibility at various objects and the use of standard software. A lot of work was done to form a homogeneous archive of waveforms and an inventory of metadata for seismic stations, which resulted in the possibility of including the GS RAS in the international centers for processing geophysical information based on FDSN. Creation of a distributed collection and processing system using a cloud service allows abstracting from the territorial features of collecting and storing geophysical information, which increases the performance of the data access service and the degree of technical readiness of key system nodes.

Geomechanical Approach in Classification of Borehole Failures in Fractured Carbonates of Boca De Jaruco Field

This article is a continuation of the work on geomechanically calculations for optimizing the drilling of horizontal wells into the productive reservoir M at the Boca de Haruco field of the Republic of Cuba, presented in the article SPE-196897. As part of the work, an assessment of the stress state and direction was carried out using geological and geophysical information, an analysis of the pressure behavior during steam injections, cross-dipole acoustics, as well as oriented caliper data in vertical wells. After the completion of the first part of the work, the first horizontal wells were successfully drilled into the M formation. According to the recommendations, additional studies were carried out: core sampling and recording of micro-imager logging in the deviated sections. Presence of wellbore failures at the inclined sections allowed to use the method of inverse in-situ stress modeling based on image logs interpretation. The classification of wellbore failures by micro-imager logging: natural origin and violations of technogenic genesis is carried out. The type of breakout is defined. The result of the work was the determination of the stress state and horizontal stresses direction. In addition, the article is supplemented with the calculation of the maximum horizontal stress through the stress regime identifier factor.

Regional integration and 3D modeling of airborne geophysical data: Map of Geophysical Anomalies of Colombia for mineral resources, 2020 version

The Map of Geophysical Anomalies of Colombia for mineral resources, MAGC 2020 version compiles the geophysical information acquired, processed and interpreted by the Servicio Geológico Colombiano (SGC) since 2013. This information was collected via airborne platforms (aircrafts) using magnetometry and gamma spectrometry. This version covers approximately 547 960 km2 of the national territory in the Andean (North and Central), Eastern (Eastern Plains and Amazon) and Caribbean zones (Perijá mountain range). This information consists of 17 blocks of geoscientific interest, covered by flight lines separated by 500 and 1000m, for a total of more than 907 566 linear km of airborne information, acquired at a nominal altitude of 100 m above the ground, with a sampling resolution that was not previously available at this scale and coverage. This document presents the methodology for compiling, processing and representing the thematic coverage included in MAGC 2020: Map of Total field magnetic anomaly (TFMA), Map of the analytic signal (AS) and radiometric ternary map of the distribution of the relative concentrations of uranium, thorium and potassium. Furthermore, the work identifies 1079 magnetometric anomalies of interest, which were subsequently analyzed and modeled in the Map of magnetic sources modeled from magnetization vector inversion, which contains a total of 1297 magnetic bodies interpreted from these anomalies. Integration of available geological and metallogenic information with each of these bodies allow the suggestion of possible geological sources and possible exploration targets. The objectives of this study were to generate and integrate geophysical information to identify new areas of interest with regards to potential mineral resources, and to generate new geoscientific knowledge about Colombia for land-use planning.

Forecast of Prospective Oil Saturation Zones in the Devonian Carbonate Deposits of the Kharyaginsky Field Based on Geological and Geophysical Information Analysis by Using Machine Learning Methods

The Kharyaginskoye oil field is located on the territory of the Nenets Autonomous District and belongs to the Timan-Pechora Basin oil and gas province. The main object of development is a Devonian age carbonate reservoir. The productive zones of the studied object are mainly confined to thin bed low-porosity reservoirs with a complex structure of void space. The high heterogeneity of deposits laterally and the presence of different levels of oil-water contact (OWC) in the marginal isolated zones necessitate a more accurate assessment of the oil-saturated effective thicknesses. The increase in the reliability of the interpretation was achieved by the joint analysis of borehole and seismic studies using Machine Learning methods. At the stage of configuring the facies model based on well logs and core data, a Multi-Resolution Graph-based Clustering MRGC was used, which provides effective integration of geological and geophysical information. The multi-dimensional dot-pattern recognition method based on k-Nearest neighbors algorithm (k-NN), and by combining various criteria, it allows solving the problem of non-linearity of the relationships between logging responses and the corresponding lithology. The algorithm of the democratic association of neural networks DNNA was used to propagate electrofacies in the inter-well space. The method optimizes the use of seismic data before summation and after summation together with well data through a controlled process that provides a calibrated and scaled distribution of facies. The most probable facies distribution can be used directly as a property in reservoir modeling or as a constraint for modeling. It is known that there is no direct connection between a certain type of wave pattern and the lithological composition of rocks, therefore, the analysis of changing reflection characteristics is performed in conjunction with geophysical data, such as well logging. In addition, a priori geological information about the work area is involved. An important condition for the effective application of facies analysis is the presence of representative core material and the availability of high-quality well information. At the first stage of the work, the lithotyping of carbonate deposits was performed according to the macro description of the core, based on the classification of limestones according to R. H. Dunham. Then, using the multidimensional statistical recognition algorithm MRGC, the relationships between the selected lithotypes and logging responses were obtained. As a result of the tuning, a cluster model was obtained that allows us to distinguish electrofacies characterized by an increased filtration and capacitance potential. At the second stage, the obtained electrofacies, considering the nature of saturation, were used to train cubes of seismic attributes and calculate the cubes of lithofacies and the probability of the existence of each lithofacies. The key point in the distribution was the use of electrofacies obtained in wells belonging to different facies zones. Thus, the joint analysis of all available borehole and seismic information by machine learning methods made it possible to make a forecast lithofacies considering the type of saturation based on geological and geophysical information analysis. The effectiveness of the presented technologies was demonstrated by analyzing the properties of low-permeable carbonate reservoirs, where classical attributes and inversion demonstrate limitations in describing a heterogeneous saturation model. The use of neural network approaches allows to configure complex nonlinear dependencies that are not available to classical methods. The use of a small volume of multi-scale geological and geophysical information using Machine Learning algorithms in the field of field-geophysical and seismic interpretation makes it possible to increase the reliability of interpretation and clarify the location of prospective zones with improved reservoir properties on the studied area, as well as to minimize geological risks during subsequent well placement.

GEW personal account: software and technological environment for storing, processing and providing results of regional geological-geophysical and geological surveying works on regional study of subsoil and reproduction of mineral resource base of hydrocarbon raw materials

The article discusses a software and technological environment designed for storing, processing and providing results of regional geological-geophysical and geological surveying works on regional study of subsoil and reproduction of the mineral resource base of hydrocarbon raw materials. The article describes the user workplaces organized for collecting, processing and evaluation of materials on approved GEW projects and final material transmitting for further storing at the Federal State Budgetary Institution «Rosgeolfond». It describes the main functionality and user interface, communication with Unified Bank of Geological and Geophysical Information of VNIGNI (UDB VNIGNI). It also describes directions of further development.

Earth Science Week to make a splash

Geoscientists have important roles in the management of the world's water at local, regional, national, and global scales. Geophysical information is critical to ensure that people have enough water for domestic, agricultural, industrial, and other needs. Given the current challenges of water management, it has never been more critical to promote awareness of water's place in earth system science. To encourage everyone to understand, conserve, and protect water, Earth Science Week 2021 will be held 10–16 October.

Features of the geological structure, tectonic development and oil and gas potential of the Chezhen depression (Bohai bay basin)

Background. In terms of oil and gas, the territory of the Chezhen depression has been studied insufficiently compared to the neighbouring same-range depressions. These depressions complicate the first-order Jiyang depression, geographically coinciding with the largest Shengli hydrocarbon field. In recent years, much geological and geophysical information about the oil geologyof the Chezhen depression has been accumulated, which allows its prospecting oil and gas potential to be assessed.Aim. To reveal regular features of the geological structure and location of oil deposits in the Chezhen depression in order to support the prospecting and exploration work within the Chezhen block of the Shengli field.Materials and methods. A comprehensive analysis of literature data and collected materials was conducted. A historical and geodynamic study of the evolution of the studied area according to literature data was carried out, along with an analysis of the most recent geological and geophysical information and exploration data based on the materials of the “Shengli AKOO Sinopek” oil company. The analysis was based on the data from 52 drilling wells and the results of seismic surveys performed in the central part of the Chezhen depression.Results. Specific features of the block geological structure of the area under study were established, which formed under the repeated influence of large-scale horizontal tectonic movements occurring at different periods of geological history. The role of the most recent fault system in the modern spatial distribution of oil deposits was determined.Conclusions. Our studies demonstrate a great prospecting potential of the Chezhen depression territory, where the discovery of new industrial oil deposits can be expected.

Developing effective subsoil reference model for seismic microzonation studies.

A general methodological approach is here discussed to integrate geological and geophysical information in seismic microzonation studies. In particular, the methodology aims at maximizing the exploitation of low-cost data for extensive preliminary assessment of ground motion amplification phenomena induced by the local seismostratigraphical configuration. Three main steps are delineated: a) the combination of geological/geomorphological analyses to develop an Engineering-Geological Model of the study area; b) targeted geophysical prospecting to provide an Engineering-Geological/Geophysical Model; c) evaluating effectiveness of Engineering-Geological/Geophysical Model by estimating expected ground motion amplification phenomena by the use of suitable computational tools. The workflow is illustrated by a case-study based on a set of villages in the Umbro-Marchean Apennine (Central Italy) damaged during the Seismic sequence occurred in Central Italy during 2016–2017.