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Integrated Approaches for Unconventional Oil and Gas Extraction and Exploration

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "H: Geo-Energy".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 15908

Special Issue Editor


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Guest Editor
Faculty of Natural Sciences, Institute of Earth Sciences, University of Silesia in Katowice, Będzińska 60, Sosnowiec, Poland
Interests: unconventional resources (coal bed methane) of hydrocarbons; coal mine methane emissions; coal petrology; coal properties; geothermal energy; economic geology of fossil fuels

Special Issue Information

Dear Colleagues,

Unconventional resources of crude oil and natural gas, while requiring specific and often costly mining technology, are a very important supplement to the existing resource base (conventional) of these raw materials. It is estimated that the resources of shale gas, tight gas and coal bed methane are up to several times greater than the resources of conventional deposits. At present, the USA—a leader in the development of unconventional oil and gas deposits covers them over 80% of the all production of oil and gas, thus it is ranked 1st place in the world in the production of hydrocarbons. Also in other countries, such as Australia or China, the exploitation of unconventional oil and gas resources is developing. However, in many other places in the world, e.g. in Europe, the development of this type of oil and gas production encounters numerous problems which significantly inhibit the effective extraction of hydrocarbons from unconventional sources. Constant research, development and implementation of new technologies for obtaining resources of unconventional hydrocarbon and taking into account external factors, e.g. environmental and social, may contribute to increasing the extraction of oil and gas from unconventional sources and thus delay the depletion of total resources, moreover unconventional gas may be a fuel transition between traditional (coal) and renewable energy sources. This special issue aims to collect scientific papers on topics related to the natural conditions of unconventional hydrocarbon resources (shale gas, tight gas, coal bed methane, shale and tight oil, tar sands, deep gas and methane clathrates), their origin, properties of reservoirs, production technology (hydraulic fracturing), processing, resources management, environmental and social issues and also spatial development of the areas of unconventional oil and gas exploitation.

Dr. Slawomir Kędzior
Guest Editor

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Keywords

  • coal bed methane & coal seam gas
  • shale gas and oil
  • tight gas and oil
  • tar sands and heavy oil
  • deep gas
  • methane clathrates
  • natural occurrence of unconventional oil and gas
  • spatial modeling of hydrocarbon basins
  •  geochemical and petrographic properties of source rocks (DOM)
  • reservoir properties of rocks
  • geomechanics
  • aquifers and well dewatering
  • production technologies (hydraulic fracturing)
  • well completion and stimulation
  • processing
  • resources management
  • environmental and social impact
  • spatial development of the exploitation area

Published Papers (11 papers)

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Research

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25 pages, 45016 KiB  
Article
Optimization of Financial Indicators in Shale-Gas Wells Combining Numerical Decline Curve Analysis and Economic Data Analysis
by Andres Soage, Ruben Juanes, Ignasi Colominas and Luis Cueto-Felgueroso
Energies 2024, 17(4), 864; https://doi.org/10.3390/en17040864 - 12 Feb 2024
Viewed by 740
Abstract
We present a methodology to determine optimal financial parameters in shale-gas production, combining numerical simulation of decline curves and stochastic modeling of the gas price. The mathematical model of gas production considers free gas in the pore and the gas adsorbed in kerogen. [...] Read more.
We present a methodology to determine optimal financial parameters in shale-gas production, combining numerical simulation of decline curves and stochastic modeling of the gas price. The mathematical model of gas production considers free gas in the pore and the gas adsorbed in kerogen. The dependence of gas production on petrophysical parameters and stimulated permeability is quantified by solving the model equations in a 3D geometry representing a typical fractured shale well. We use Monte Carlo simulation to characterize the statistical properties of various common financial indicators of the investment in shale-gas. The analysis combines many realizations of the physical model, which explores the variability of porosity, induced permeability, and fracture geometry, with thousands of realizations of gas price trajectories. The evolution of gas prices is modeled using the bootstrapping statistical resampling technique to obtain a probability density function of the initial price, the drift, and the volatility of a geometric Brownian motion for the time evolution of gas price. We analyze the Net Present Value (NPV), Internal Rate of Return (IRR), and Discounted Payback Period (DPP) indicators. By computing the probability density function of each indicator, we characterize the statistical percentile of each value of the indicator. Alternatively, we can infer the value of the indicator for a given statistical percentile. By mapping these parametric combinations for different indicators, we can determine the parameters that maximize or minimize each of them. We show that, to achieve a profitable investment in shale-gas with high certainty, it is necessary to place the wells in extremely good locations in terms of geological parameters (porosity) and to have exceptional fracturing technology (geometry) and fracture permeability. These high demands in terms of petrophysical properties and hydrofracture engineering may explain the industry observation of “sweet spots”, that is, specific areas within shale-gas plays that tend to yield more profitable wells and where many operators concentrate their production. We shed light on the rational origin of this phenomenon: while shale formations are abundant, areas prone to having a multi-parameter combination that renders the well profitable are less common. Full article
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21 pages, 3801 KiB  
Article
Chemostratigraphic Approach to the Study of Resources’ Deposit in the Upper Silesian Coal Basin (Poland)
by Ewa Krzeszowska
Energies 2024, 17(3), 642; https://doi.org/10.3390/en17030642 - 29 Jan 2024
Viewed by 502
Abstract
The Upper Silesian Coal Basin (USCB), located in southern Poland, is the major coal basin in Poland, and all technological types of hard coal, including coking coal, are exploited. It is also an area of high potential for coal-bed methane (CBM). Despite the [...] Read more.
The Upper Silesian Coal Basin (USCB), located in southern Poland, is the major coal basin in Poland, and all technological types of hard coal, including coking coal, are exploited. It is also an area of high potential for coal-bed methane (CBM). Despite the increasing availability of alternative energy sources globally, it is a fact that the use of fossil fuels will remain necessary for the next few decades. Therefore, research on coal-bearing formations using modern research methods is still very important. The application of geochemistry and chemostratigraphy in reservoir characterization has become increasingly common in recent years. This paper presents the possibility of applying chemostratigraphic techniques to the study of the Carboniferous coal-bearing succession of the Upper Silesian Coal Basin. The material studied comes from 121 core samples (depth 481–1298 m), representing the Mudstone Series (Westphalian A, B). Major oxide concentrations of Al2O3, SiO2, Fe2O3, P2O5, K2O, MgO, CaO, Na2O, K2O, MnO, TiO2, and Cr2O3 were obtained using X-ray fluorescence (XRF) spectrometry. Trace elements were analyzed using inductively coupled plasma mass spectrometry (ICP/MS). The geochemical record from the Mudstone Series shows changes in the concentration of major elements and selected trace elements, leading to the identification of four chemostratigraphic units. These units differ primarily in the content of Fe, Ca, Mg, Mn, and P as well as the concentration of Zr, Hf, Nb, Ta, and Ti. The study also discusses quartz origin (based on SiO2 and TiO2), sediment provenance and source-area rock compositions (based on Al2O3/ TiO2, TiO2/Zr, and La/Th), and paleoredox conditions (based on V/Cr, Ni/Co, U/Th, (Cu+Mo)/Zn, and Sr/Ba) for the chemostratigraphic units. Chemostratigraphy was used for the first time in the study of the Carboniferous coal-bearing series of the USCB, concluding that it can be used as an effective stratigraphic tool and provide new information on the possibility of correlating barren sequences of the coal-bearing succession. Full article
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14 pages, 3319 KiB  
Article
The Impact of Atmospheric Pressure Changes on Methane Emission from Goafs to Coal Mine Workings
by Adam Duda
Energies 2024, 17(1), 173; https://doi.org/10.3390/en17010173 - 28 Dec 2023
Viewed by 530
Abstract
Increased effectiveness of methane drainage from sealed post-mining goaves in hard coal mines contributes to reduced methane emission from goaves into the mine ventilation system. This paper focuses on issues concerning the assessment of the additional amount of methane released from the goaf [...] Read more.
Increased effectiveness of methane drainage from sealed post-mining goaves in hard coal mines contributes to reduced methane emission from goaves into the mine ventilation system. This paper focuses on issues concerning the assessment of the additional amount of methane released from the goaf into mine workings during periods of atmospheric pressure drops, which can be captured with a methane drainage system. Thanks to the solutions presented in the paper, it is possible to control the efficiency of the goaf drainage system, which in turn leads to the reduction of methane emission from the mine ventilation air into Earth’s atmosphere. These solutions are of great added value for both the environment and coal mines as they reduce the costs arising from greenhouse gas emissions that are incurred by mining companies, increasing the efficiency of methane capture and its use in gas engines or district heating systems. The paper uses relationships relating to the influence of atmospheric pressure changes on the process of gas release from the goaf according to the hysteresis loop of methane release during atmospheric pressure changes, which was developed based on conducted research. The analysis and conclusions presented in this paper may facilitate the development of strategies aimed at reducing methane emissions from a mine’s ventilated air into Earth’s atmosphere. Full article
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22 pages, 5499 KiB  
Article
A Well Production Prediction Method of Tight Reservoirs Based on a Hybrid Neural Network
by Fuquan Song, Heying Ding, Yongzheng Wang, Shiming Zhang and Jinbiao Yu
Energies 2023, 16(6), 2904; https://doi.org/10.3390/en16062904 - 21 Mar 2023
Viewed by 1532
Abstract
Tight reservoirs have poor physical properties: low permeability and strong heterogeneity, which makes it difficult to predict productivity. Accurate prediction of oil well production plays a very important role in the exploration and development of oil and gas reservoirs, and improving the accuracy [...] Read more.
Tight reservoirs have poor physical properties: low permeability and strong heterogeneity, which makes it difficult to predict productivity. Accurate prediction of oil well production plays a very important role in the exploration and development of oil and gas reservoirs, and improving the accuracy of production prediction has always been a key issue in reservoir characterization. With the development of artificial intelligence, high-performance algorithms make reliable production prediction possible from the perspective of data. Due to the high cost and large error of traditional seepage theory formulas in predicting oil well production, this paper establishes a horizontal well productivity prediction model based on a hybrid neural network method (CNN-LSTM), which solves the limitations of traditional methods and produces accurate predictions of horizontal wells’ daily oil production. In order to prove the effectiveness of the model, compared with the prediction results of BPNN, RBF, RNN and LSTM, it is concluded that the error results of the CNN-LSTM prediction model are 67%, 60%, 51.3% and 28% less than those of the four models, respectively, and the determination coefficient exceeds 0.95. The results show that the prediction model based on a hybrid neural network can accurately reflect the dynamic change law of production, which marks this study as a preliminary attempt of the application of this neural network method in petroleum engineering, and also provides a new method for the application of artificial intelligence in oil and gas field development. Full article
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23 pages, 6509 KiB  
Article
Optimization of CO2 Huff-n-Puff in Unconventional Reservoirs with a Focus on Pore Confinement Effects, Fluid Types, and Completion Parameters
by Aaditya Khanal and Md Fahim Shahriar
Energies 2023, 16(5), 2311; https://doi.org/10.3390/en16052311 - 28 Feb 2023
Cited by 4 | Viewed by 1473
Abstract
The cyclic injection of CO2, referred to as the huff-n-puff (HnP) method, is an attractive option to improve oil recovery from unconventional reservoirs. This study evaluates the optimization of the CO2 HnP method and provides insight into the aspects of [...] Read more.
The cyclic injection of CO2, referred to as the huff-n-puff (HnP) method, is an attractive option to improve oil recovery from unconventional reservoirs. This study evaluates the optimization of the CO2 HnP method and provides insight into the aspects of CO2 sequestration for unconventional reservoirs. Furthermore, this study also examines the impact of nanopore confinement, fluid composition, injection solvent, diffusivity parameters, and fracture properties on the long-term recovery factor. The results from over 500 independent simulations showed that the optimal recovery is obtained for the puff-to-huff ratio of around 2.73 with a soak period of fewer than 2.7 days. After numerous HnP cycles, an optimized CO2 HnP process resulted in about 970-to-1067-ton CO2 storage per fracture and over 32% recovery, compared to 22% recovery for natural depletion over the 30 years. The optimized CO2 HnP process also showed higher effectiveness compared to the N2 HnP scenario. Additionally, for reservoirs with significant pore confinement (pore size ≤ 10 nm), the oil recovery improved by over 3% compared to the unconfined bulk phase properties. We also observed over 300% improvement in recovery factor for a fluid with a significant fraction of light hydrocarbons (C1–C6), compared to just a 50% improvement in recovery for a fluid with a substantial fraction of heavy hydrocarbons (C7+). Finally, the results also showed that fracture properties are much more important for CO2 HnP than natural depletion. This study provides critical insights to optimize and improve CO2 HnP operations for different fluid phases and fracture properties encountered in unconventional reservoirs. Full article
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25 pages, 14574 KiB  
Article
Suitability of Different Machine Learning Outlier Detection Algorithms to Improve Shale Gas Production Data for Effective Decline Curve Analysis
by Taha Yehia, Ali Wahba, Sondos Mostafa and Omar Mahmoud
Energies 2022, 15(23), 8835; https://doi.org/10.3390/en15238835 - 23 Nov 2022
Cited by 8 | Viewed by 1943
Abstract
Shale gas reservoirs have huge amounts of reserves. Economically evaluating these reserves is challenging due to complex driving mechanisms, complex drilling and completion configurations, and the complexity of controlling the producing conditions. Decline Curve Analysis (DCA) is historically considered the easiest method for [...] Read more.
Shale gas reservoirs have huge amounts of reserves. Economically evaluating these reserves is challenging due to complex driving mechanisms, complex drilling and completion configurations, and the complexity of controlling the producing conditions. Decline Curve Analysis (DCA) is historically considered the easiest method for production prediction of unconventional reservoirs as it only requires production history. Besides uncertainties in selecting a suitable DCA model to match the production behavior of the shale gas wells, the production data are usually noisy because of the changing choke size used to control the bottom hole flowing pressure and the multiple shut-ins to remove the associated water. Removing this noise from the data is important for effective DCA prediction. In this study, 12 machine learning outlier detection algorithms were investigated to determine the one most suitable for improving the quality of production data. Five of them were found not suitable, as they remove complete portions of the production data rather than scattered data points. The other seven algorithms were deeply investigated, assuming that 20% of the production data are outliers. During the work, eight DCA models were studied and applied. Different recommendations were stated regarding their sensitivity to noise. The results showed that the clustered based outlier factor, k-nearest neighbor, and the angular based outlier factor algorithms are the most effective algorithms for improving the data quality for DCA, while the stochastic outlier selection and subspace outlier detection algorithms were found to be the least effective. Additionally, DCA models, such as the Arps, Duong, and Wang models, were found to be less sensitive to removing noise, even with different algorithms. Meanwhile, power law exponential, logistic growth model, and stretched exponent production decline models showed more sensitivity to removing the noise, with varying performance under different outlier-removal algorithms. This work introduces the best combination of DCA models and outlier-detection algorithms, which could be used to reduce the uncertainties related to production forecasting and reserve estimation of shale gas reservoirs. Full article
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16 pages, 8176 KiB  
Article
3D Geomechanical Model Construction for Wellbore Stability Analysis in Algerian Southeastern Petroleum Field
by Said Eladj, Mohamed Zinelabidine Doghmane, Tanina Kenza Lounissi, Mabrouk Djeddi, Kong Fah Tee and Sofiane Djezzar
Energies 2022, 15(20), 7455; https://doi.org/10.3390/en15207455 - 11 Oct 2022
Cited by 8 | Viewed by 1853
Abstract
The main objective of this research work was the wellbore stability evaluation of oil and gas wells based on a 3D geomechanical model, which as constructed using seismic inversion in a southeastern Algerian petroleum field. The seismic inversion model was obtained by using [...] Read more.
The main objective of this research work was the wellbore stability evaluation of oil and gas wells based on a 3D geomechanical model, which as constructed using seismic inversion in a southeastern Algerian petroleum field. The seismic inversion model was obtained by using an iterative method and Aki and Richards approximation. Since the correlation between the inversion model and the log data was high at the wells, the reservoir was efficiently characterized and its lithology carefully discriminated in order to build a reliable 3D geomechanical model. The latter was further used to suggest the drilling mud weight window for the ongoing wells (well 5) and to examine the stability of four previously drilled wells. The main contribution of this study is providing a 3D geomechanical model that allows the optimization of drilling mud weight parameters so that a wellbore’s stability is guaranteed, on the one hand, and, on the other hand, so that the reservoir damage brought about by excessive surfactant use can be prevented. Indeed, the mud parameters are not just important for the drilling process’s effectiveness but also for logging operations. Since the tools have limited investigation diameters, with excessive use of surfactant, the invaded zone can become larger than the tools’ investigation diameter, which makes their logs unreliable. Hence, the 3D geomechanical model presented here is highly recommendable for the proposition of new wells, entailing less exploration uncertainty and more controllable productivity. Full article
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18 pages, 3682 KiB  
Article
Geological and Mining Factors Controlling the Current Methane Conditions in the Rydułtowy Coal Mine (Upper Silesian Coal Basin, Poland)
by Sławomir Kędzior and Marcin Dreger
Energies 2022, 15(17), 6364; https://doi.org/10.3390/en15176364 - 31 Aug 2022
Cited by 4 | Viewed by 1186
Abstract
Methane emissions into mine workings and the atmosphere are still a significant environmental and work safety problem. Since 2000, the Rydułtowy coal mine, located in the western part of the Upper Silesian Coal Basin, has been struggling with significant methane emissions compared to [...] Read more.
Methane emissions into mine workings and the atmosphere are still a significant environmental and work safety problem. Since 2000, the Rydułtowy coal mine, located in the western part of the Upper Silesian Coal Basin, has been struggling with significant methane emissions compared to the previous period. The distribution of the methane content in coal seams was analysed, and the factors that influenced it were reviewed. Then, the annual variability in methane emissions in mining excavations was investigated, and the depth of coal extraction was linked to methane conditions and the time of mining works. It has been shown that the currently observed distribution of methane in coal seams is the result of, inter alia, the geological development of the western part of the basin, the lithological character of coal-bearing Carboniferous deposits and overburden, and fault tectonics. The sorption capacity of coal seams decreases with increasing temperature and the coal rank. The amount of methane emitted into mine workings depends mainly on the methane content in the coal seams in mining sites and on the sorption capacity of the coal seams. The depth of exploitation, increasing from year to year, leads to an increase in the methane content in coal seams and a simultaneous decrease in the sorption capacity of coal, which will result in higher methane emissions in the future. Full article
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16 pages, 3342 KiB  
Article
The Young’s Modulus and Poisson’s Ratio of Hard Coals in Laboratory Tests
by Mirosława Bukowska, Piotr Kasza, Rafał Moska and Janusz Jureczka
Energies 2022, 15(7), 2477; https://doi.org/10.3390/en15072477 - 28 Mar 2022
Cited by 3 | Viewed by 2317
Abstract
The Young’s modulus and Poisson’s ratio, parameters reflecting the elastic response of a rock to stress, are the key parameters used in many engineering activities, such as hard coal mining and natural gas extraction. The objective of this paper was to present the [...] Read more.
The Young’s modulus and Poisson’s ratio, parameters reflecting the elastic response of a rock to stress, are the key parameters used in many engineering activities, such as hard coal mining and natural gas extraction. The objective of this paper was to present the results of complex laboratory measurements of the static and dynamic Young’s modulus and Poisson’s ratio for Upper Carboniferous hard coals from the Upper Silesian Coal Basin. The coals differed in geologic age (Mudstone Series—younger coals; Upper Silesian Sandstone Series—older coals) and petrographic structure (vitrain, clarain, and durain lithotype). Elastic parameters of the coals were determined following compression tests under a complex state of stress, as well as using the ultrasonic method in reservoir conditions. On this basis, linear functional dependences between parameters such as UCS, differential stress, confining pressure, strain rate, P- and S-wave velocities, and the static and dynamic Young’s modulus and Poisson’s ratio were determined. These dependences turned out to be linear, with strong and very strong correlation, as indicated by the high coefficients of determination, R2. These new results significantly broaden the knowledge of elastic properties of Carboniferous hard coals, especially in the field of geoengineering, underground coal gasification, and reservoir stimulation for coal bed methane extraction. Full article
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Review

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23 pages, 1567 KiB  
Review
Characteristics of Tight Gas Reservoirs in the Xujiahe Formation in the Western Sichuan Depression: A Systematic Review
by Jiongfan Wei, Jingong Zhang and Zishu Yong
Energies 2024, 17(3), 587; https://doi.org/10.3390/en17030587 - 25 Jan 2024
Viewed by 561
Abstract
In current energy structure adjustments, the prominence of unconventional oil and gas resources continues to grow, with increasing attention being paid to tight gas, a major component of natural gas production. The Xujiahe Formation gas reservoir in the Western Sichuan Depression represents a [...] Read more.
In current energy structure adjustments, the prominence of unconventional oil and gas resources continues to grow, with increasing attention being paid to tight gas, a major component of natural gas production. The Xujiahe Formation gas reservoir in the Western Sichuan Depression represents a typical tight gas reservoir and the study of its reservoir characteristics is a key focus for current and future exploration and development efforts. This review employs the PRISMA method to screen and integrate the primary findings of 26 documents spanning the period from 2008 to 2023, with the aim of providing a comprehensive overview of the progress and outcomes of research on the tight gas reservoir characteristics of the Xujiahe Formation in the Western Sichuan Depression. The selected research documents summarize the characteristics of the Xujiahe Formation tight gas reservoir in the Western Sichuan Depression from four perspectives: lithology, physical properties, reservoir space, and the main factors influencing reservoir quality. Through a review of these previous studies, it is evident that existing research has predominantly focused on the relationship between diagenesis and reservoir densification, indicating certain limitations. We also delve into the characteristics of tight gas sandstone reservoirs in the study area, considering their depositional systems, fracture development, cementation, and impact on the exploration and development of tight gas reservoirs. Additionally, we propose measures to stabilize and enhance tight gas production in the Xujiahe Formation in the Western Sichuan Depression. Moreover, we outline the next steps for further research and exploration. Full article
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16 pages, 5876 KiB  
Review
Electromagnetic Surveys for Petroleum Exploration: Challenges and Prospects
by Igor Buddo, Ivan Shelokhov, Natalya Misyurkeeva, Maxim Sharlov and Yury Agafonov
Energies 2022, 15(24), 9646; https://doi.org/10.3390/en15249646 - 19 Dec 2022
Cited by 3 | Viewed by 2180
Abstract
Transient electromagnetic (TEM) surveys constitute an important element in exploration projects and can be successfully used in the search for oil and gas. Different modifications of the method include shallow (sTEM), 2D, 3D, and 4D (time-lapse) soundings. TEM data allow for solving a [...] Read more.
Transient electromagnetic (TEM) surveys constitute an important element in exploration projects and can be successfully used in the search for oil and gas. Different modifications of the method include shallow (sTEM), 2D, 3D, and 4D (time-lapse) soundings. TEM data allow for solving a large scope of problems for estimating resources and reserves of hydrocarbons, discriminating reservoir rocks, detecting tectonic features, and characterizing drilling conditions. TEM surveys are applicable at all stages, from initial prospecting to production, and are especially efficient when combined with seismic surveys. Each stage has its specific objectives: estimation of net pay thickness, porosity, and fluid type during prospecting, optimization of well placement and prediction of drilling conditions in exploration, and monitoring of flooding during production. Electromagnetic soundings resolve permafrost features well and thus have a high potentiality for exploration in the Arctic petroleum province. At the first reconnaissance stage of regional prospecting in East Siberia, electromagnetic and seismic data were used jointly to map the junction of the Aldan basin (part of the Aldan-Maya foredeep) with the eastern slope of the Aldan uplift and to constrain the limits of Neoproterozoic sediments. The TEM-based images revealed reservoir rocks in the Upper and Middle Neoproterozoic strata. TEM data have implications for the amount of in-place oil and gas resources in prospects, leads, and plays (Russian categories D1–3) at the prospecting and exploration stages and contingent recoverable reserves (C2) during exploration (latest stage). The contribution of the TEM survey to oil and gas evaluation is quantified via economic variables, such as the value of information (VOI) and expected monetary value (EMV). Full article
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