Energy Sector Research Articles

Restoring trust in ESG investing through the adoption of just transition ethics

The prominent growth in environmental, social and governance (ESG) investment is evident, with the number of global assets managed sustainably more than doubled over the last decade. This trend is expected to continue until 2030. This type of financial data is positive but given the United Nations stated 'climate emergency' and 'climate survival' in society today, there needs to be an even greater acceleration of growth in ESG investment. Unfortunately, significant negativity has emerged on ESG in recent years. This 'Cutting Edge' study explores the reasons why and how ESG investment has veered off the journey towards enabling society to achieve both its targets under the 2030 United Nations Sustainable Energy Agenda and the 2015 Paris Agreement. It examines the factors prompting leading multinational companies, particularly in the energy and food sectors, to shift their corporate strategies. The key message advanced is that ESG frameworks and guidelines are not problematic; rather, the issue lies in the practice of ethics in decision-making within corporations. Addressing this ethical challenge, which is at the heart of ESG practices, across different professions and disciplines can rebuild trust among stakeholders in ESG investing. This form of interdisciplinary ‘just transition ethics' can re-orient us back on the journey towards a just and sustainable world.

The effect of structural oil shocks on stock returns of Indian renewable energy companies across market conditions

Purpose This study aims to evaluate the structural oil shocks effect on stock returns of Indian renewable energy companies across market conditions. Design/methodology/approach This study applies the structural vector autoregression model to estimate sources of oil shocks such as oil supply shock, aggregate demand shock and oil price-specific demand shock. In the next step, the panel quantile regression model estimates the effect of these oil shocks on stock return across market conditions. Monthly data are collected from January 2009 to December 2019. All renewable energy companies listed on the National Stock Exchange of India are considered for the analysis. Findings In the whole sample analysis, this study finds that oil shocks negatively affect stock returns in most of the market conditions except oil price-specific demand shock. In sub-groups, oil shocks driven by supply and aggregate demand also negatively affect stock return in most market conditions. This study finds the positive interaction of oil price-specific demand shock. A majority of these positive interactions happen in bearish market conditions. In the whole sample, the asymmetric effects of shocks driven from oil supply and oil price-specific demand are seen in most quantiles or market conditions. At the same time, aggregate demand shock does not affect asymmetrically. In the sub-group analysis, standalone renewable energy companies stock returns are least asymmetrically affected by these oil shocks. The asymmetries of oil supply-driven shock on stock returns of the renewable energy sub-group companies are found in most quantiles. Originality/value First, this is a company-level study of the stock returns response to the structural oil shocks in the renewable energy sector. Second, to the best of the authors’ knowledge, this type of study is the first in the Indian context. Third using panel quantile regression model along with capital asset pricing model framework, the authors investigate these effects across market conditions.

Some inconvenient truths about decarbonization, the hydrogen economy, and power-to-X technologies

The decarbonization of the energy sector has been a subject of research and of political discussions for several decades, gaining significant attention in the last years. It is commonly acknowledged that the most obvious way to achieve decarbonization is the use of renewable energy sources.Within the context of the energy sector decarbonization, many mainly industrialized countries recently started developing national plans to establish a hydrogen-based economy in the very near future. The plans for green hydrogen initially try to (a) target sectors that are difficult to decarbonize and (b) address issues related to the storage and transportation of CO2-free energy.To achieve almost complete decarbonization, electric power must be generated exclusively from renewable sources. In so-called Power-to-X (PtX) technologies, green hydrogen is generated from electricity and subsequently converted to another energy carrier which can be further stored, transported and used. In PtX, X stands, for example, for liquid hydrogen, methanol or ammonia.The challenges associated with decarbonization include those associated with (a) the expansion of renewable energies (e.g., high capital demand, political and social issues), (b) the production, transportation, and storage of hydrogen and the energy carriers denoted by X in PtX (e.g., high cost and low overall efficiency), and (c) the expected significant increase in the demand for electrical energy. The paper discusses whether and under which conditions the current national and international hydrogen plans of many industrialized countries could lead to a maximization of decarbonization in the world. It concludes that, in general, as long as the conditions for generating large excess amounts of green electricity are not met, the quick establishment of a hydrogen economy could not only be very expensive, but also counterproductive to the worldwide decarbonization efforts.

Industry-specific stock valuation methods – a literature review

PurposeSurprisingly little is known of the various methods of security analysis used by financial analysts with industry-specific knowledge. Financial analysts’ industry knowledge is a favored and appreciated attribute by fund managers and institutional investors. Understanding analysts’ use of industry-specific valuation models, which are the main value drivers within different industries, will enhance our understanding of important aspects of value creation in these industries. This paper contributes to the broader understanding of how financial analysts in various industries approach valuation, offering insights that can be beneficial to a wide range of stakeholders in the financial market.Design/methodology/approachThis paper systematically reviews existing research to consolidate the current understanding of analysts’ use of valuation models and factors. It aims to demystify what can often be seen as a “black box”, shedding light on the valuation tools employed by financial analysts across diverse industries.FindingsThe use of industry-specific valuation models and factors by analysts is a subject of considerable interest to both academics and investors. The predominant model in several industries is P/E, with some exceptions. Notably, EV/EBITDA is favored in the telecom, energy and materials sectors, while the capital goods industry primarily relies on P/CF. In the REITs sector, P/AFFO is the most commonly employed model. In specific sectors like pharmaceuticals, energy and telecom, DCF is utilized. However, theoretical models like RIM and AEG find limited use among analysts.Originality/valueThis is the first paper systematically reviewing the research on analyst’s use of industry-specific stock valuation methods. It serves as a foundation for future research in this field and is likely to be of interest to academics, analysts, fund managers and investors.

Assessing the impact of renewable energy policies on decarbonization in developing countries

This study offers the first consistent attempt to identify how energy sector decarbonization policies have affected the energy mix over the last four decades across more than 100 developing countries. It applies systematic regression analysis to five energy sector decarbonization outcomes and 75+ policy instruments aggregated into seven policy packages. Combining instrumental variables with country interactions and country and time-fixed effects in regional panels helps address potential endogeneity issues. Only a handful of energy policy packages significantly affect decarbonizing developing countries' energy mix, and they more often achieve a negligible or opposite result than intended three years after implementation. Policies that address counterparty risk have the highest immediate effect. Effects of renewable policies on different decarbonization outcomes improve slightly five and seven years after their implementation.

A Reviewed Turn at of Methods for Determining the Type of Fault in Power Transformers Based on Dissolved Gas Analysis

Since power transformers are the most important pieces of equipment in electricity transmission and distribution systems, special attention must be paid to their maintenance in order to keep them in good condition for a long time. This paper reviews the main steps in the process of diagnosing the health of power transformer insulation, which involves the science of analysing the gases dissolved in power transformer oil for effective identification of faults. An accurate diagnosis of incipient faults is favourable to sustainable development and necessary to maintain a reliable supply of electricity. The methods presented for fault diagnosis in mineral-oil-immersed power transformers are divided into analytical and graphical methods and have been found to be simple, economical and effective. After describing the methods, both their strengths and weaknesses were identified, and over the years, the methods were complemented to provide highly accurate information, validated by field inspections. This paper focuses on practical information and applications to manage maintenance based on accurate and up-to-date data. The contents of this paper will be of particular use to engineers who manufacture, monitor and/or use high-power transformers in the energy sector, as well as to undergraduate, master’s and PhD students interested in such applications.

Driving innovation in energy and telecommunications: next-generation energy storage and 5G technology for enhanced connectivity and energy solutions

Driving innovation in energy and telecommunications involves leveraging next-generation energy storage and 5G technology to enhance connectivity and energy solutions. This review explores the intersection of these two domains, highlighting the importance of advancements in energy storage and 5G technology for a sustainable and connected future. Energy storage is crucial for balancing the supply and demand of electricity in modern power systems. Traditional energy storage methods, such as batteries and pumped hydro, have limitations in terms of scalability, efficiency, and cost-effectiveness. Next-generation energy storage technologies, including advanced batteries, hydrogen storage, and thermal storage, offer promising solutions to overcome these limitations. These technologies enable efficient energy storage at scale, facilitating the integration of renewable energy sources like solar and wind into the grid. By storing excess energy generated during periods of low demand, next-generation energy storage systems ensure a reliable and stable power supply, reducing the reliance on fossil fuels and lowering greenhouse gas emissions. In parallel, the evolution of telecommunications technology, particularly the advent of 5G networks, is revolutionizing connectivity and communication. 5G technology offers significantly higher data transfer speeds, lower latency, and increased network capacity compared to its predecessors. These capabilities are essential for supporting emerging technologies such as the Internet of Things (IoT), autonomous vehicles, and smart grids. With 5G-enabled IoT devices, utilities can monitor energy consumption in real-time, optimize grid operations, and detect and respond to faults more efficiently. Moreover, 5G connectivity enhances the efficiency and reliability of energy storage systems by enabling seamless communication between distributed energy resources and grid operators. The convergence of next-generation energy storage and 5G technology presents numerous opportunities for driving innovation in both energy and telecommunications sectors. One of the key areas of innovation is the development of smart energy storage systems equipped with 5G connectivity. These systems can autonomously adjust their operation based on grid conditions, weather forecasts, and energy demand patterns, optimizing energy storage and distribution in real-time. Furthermore, advanced energy management algorithms leveraging artificial intelligence (AI) and machine learning (ML) algorithms can optimize energy usage and storage, further improving the efficiency and reliability of the grid. Another area of innovation lies in the integration of renewable energy resources with 5G-enabled microgrids. Microgrids are localized energy systems that can operate independently or in conjunction with the main grid. By combining renewable energy sources with energy storage and 5G-enabled communication, microgrids can provide reliable, clean, and resilient power to remote or urban areas. These microgrids can also facilitate peer-to-peer energy trading, allowing consumers to buy and sell excess energy within their communities, fostering energy independence and sustainability. Furthermore, advancements in battery technology, such as solid-state batteries and flow batteries, are enhancing the performance and reliability of energy storage systems. Solid-state batteries offer higher energy density, faster charging rates, and improved safety compared to conventional lithium-ion batteries. Flow batteries, on the other hand, provide scalability and long-duration storage capabilities, making them suitable for grid-scale applications. Integrating these advanced battery technologies with 5G-enabled monitoring and control systems enhances the overall resilience and flexibility of the energy infrastructure. In addition to technological advancements, driving innovation in energy and telecommunications requires collaboration among various stakeholders, including policymakers, regulators, industry players, and research institutions. Policies and regulations should incentivize the deployment of next-generation energy storage and 5G infrastructure, promote interoperability standards, and ensure data privacy and security. Public-private partnerships can facilitate the investment and deployment of innovative solutions, while research and development initiatives can spur further technological advancements. Driving innovation in energy and telecommunications through next-generation energy storage and 5G technology is essential for building a sustainable, connected, and resilient future. By leveraging advanced energy storage systems, smart grids, and 5G-enabled communication networks, we can optimize energy usage, reduce carbon emissions, and enhance the reliability and efficiency of our energy infrastructure. Collaboration and investment across various sectors are key to unlocking the full potential of these transformative technologies and achieving a brighter, more sustainable future for generations to come. Keywords: Innovation, Energy, Telecommunications, Next-Generation, 5G technology, Enhanced connectivity.

Optimal Gasoline Price Predictions: Leveraging the ANFIS Regression Model

This study presents an in-depth analysis of gasoline price forecasting using the adaptive network-based fuzzy inference system (ANFIS), with an emphasis on its implications for policy-making and strategic decisions in the energy sector. The model leverages a comprehensive dataset from the U.S. Energy Information Administration, spanning over 30 years of historical price data from 1993 to 2023, along with relevant temporal features. By combining the strengths of fuzzy logic and neural networks, the ANFIS approach can effectively capture the complex, nonlinear relationships present in the data, enabling reliable price predictions. The dataset’s preprocessing involved decomposing the date into year, month, and day components to enhance the model’s input features. Our methodology entailed a systematic approach to ANFIS regression, including data preparation, model training with the inclusion of the previous week’s prices as an additional feature, and rigorous performance evaluation using MSE, RMSE, and correlation coefficients. The results indicate that incorporating previous prices significantly enhances the model’s accuracy, as reflected by improved scores and correlation metrics. The findings have significant implications for the energy sector, where stakeholders can leverage the ANFIS model’s insights for strategic decision-making. Accurate gasoline price forecasts are instrumental in devising pricing strategies, managing risks associated with price volatility, and guiding policy formulation. The model’s predictive capability enables energy companies to optimize resource allocation, plan for future investments, and maintain competitive advantage in a market influenced by fluctuating prices. Moreover, policymakers can utilize these predictions to assess the impact of energy policies on market prices and consumer behavior, ensuring that regulatory measures align with market dynamics and sustainability goals. In addition to the ANFIS model, we also employed Vector Autoregression (VAR) and Autoregressive Integrated Moving Average (ARIMA) models to validate our approach and provide a comprehensive understanding of time series forecasting within the energy sector. Notably, the ANFIS model achieves a score of 0.9970 and a robust correlation of 0.9985, demonstrating its ability to accurately forecast gasoline prices based on historical data and features. The integration of these traditional techniques with advanced ANFIS modeling offers a robust framework for accurate and reliable gasoline price prediction, which is vital for informed policy-making and strategic planning in the energy industry.

Single-Atom based Metal-Organic Framework Photocatalysts for Solar-Fuel Generation.

The growing demand for fossil fuels and subsequent CO2 emissions prompted a search for alternate sources of energy and a reduction in CO2. Photocatalysis driven by solar light has been found as a potential research area to tackle both these problems. In this direction, SAC@MOF (Single-atom loaded MOFs) photocatalysis is an emerging field and a promising technology. The unique properties of single-atom catalysts (SACs), such as high catalytic activity and selectivity, are leveraged in these systems. Photocatalysis, focusing on the utilization of Metal-Organic Frameworks (MOFs) as platforms for creating single-atom catalysts (SACs) characterized by metal single-atoms (SAs) as their active sites, are noted for their unparalleled atomic efficiency, precisely defined active sites, and superior photocatalytic performance. The synergy between MOFs and SAs in photocatalytic systems is meticulously examined, highlighting how they collectively enhance photocatalytic efficiency. This review examines SAC@MOF development and applications in environmental and energy sectors, focusing on synthesis and stabilization methods for SACs on MOFs and also characterization techniques vital for understanding these catalysts. The potential of SAC@MOF in CO2 Photoreduction and Photocatalytic H2 evolution is highlighted, emphasizing its role in green energy technologies and advances in materials science and Photocatalysis.

Can China’s Regional Industrial Chain Innovation and Reform Policy Make the Impossible Triangle of Energy Attainable? A Causal Inference Study on the Effect of Improving Industrial Chain Resilience

This study used a double machine learning model (based on the random forest algorithm) and spatial Durbin DIDs model to conduct quasi-natural experiments. The results are as follows: (1) innovation and reform policy regarding regional industrial chains as well as their resilience can significantly and positively address the development of China’s impossible triangle coupling of energy; (2) implementing the innovation and reform policy for regional industrial chains in other regions can have a significant positive spatial transmission effect on the impossible triangle coupling coordinated development of energy in the region; (3) regional industrial chain resilience can produce a significant positive mediating effect between the innovation and reform policy of regional industrial chains and the safety, reliability, and economic feasibility of green and clean energy systems; (4) under the counterfactual framework, the mechanism path “innovation and reform policy of the regional industry chain→regional industry chain resilience→coordination degree of impossible triangle coupling of energy” has significantly positive direct and indirect effects in both the treatment group and the control group. However, “innovation and reform policy of the regional industrial chain→regional industrial chain resilience→the energy sector’s impossible triangle coupling coordination degree” and “innovation and reform policy of the regional industrial chain→leading power of the regional industrial chain→the energy sector’s impossible triangle coupling coordination degree” have significantly positive direct and indirect effects in the treatment group, but only the direct effect is significant in the control group.

Thermochemical Activation of Wood with NaOH, KOH and H3PO4 for the Synthesis of Nitrogen-Doped Nanoporous Carbon for Oxygen Reduction Reaction

Carbonization of biomass residues followed by activation has great potential to become a safe process for the production of various carbon materials for various applications. Demand for commercial use of biomass-based carbon materials is growing rapidly in advanced technologies, including in the energy sector, as catalysts, batteries and capacitor electrodes. In this study, carbon materials were synthesized from hardwood using two carbonization methods, followed by activation with H3PO4, KOH and NaOH and doping with nitrogen. Their chemical composition, porous structure, thermal stability and structural order of samples were studied. It was shown that, despite the differences, the synthesized carbon materials are active catalysts for oxygen reduction reactions. Among the investigated carbon materials, NaOH-activated samples exhibited the lowest Tafel slope values, of −90.6 and −88.0 mV dec–1, which are very close to the values of commercial Pt/C at −86.6 mV dec–1.

Validation Assessment of Turbulent Reacting Flow Model Using the Area-Validation Metric on Medium-Scale Methanol Pool Fire Results

Abstract Accident analysis and ensuring power plant safety are pivotal in the nuclear energy sector. Significant strides have been achieved over the past few decades regarding fire protection and safety, primarily centered on design and regulatory compliance. Yet, after the Fukushima accident a decade ago, the imperative to enhance measures against fire, internal flooding, and power loss has intensified. Hence, a comprehensive, multilayered protection strategy against severe accidents is needed. Consequently, gaining a deeper insight into pool fires and their behavior through extensive validated data can greatly aid in improving these measures using advanced validation techniques. A model validation study was performed at Sandia National Laboratories (SNL) in which a 30-cm diameter methanol pool fire was modeled using the SIERRA/Fuego turbulent reacting flow code. This validation study used a standard validation experiment to compare model results against, and conclusions have been published. The fire was modeled with a large eddy simulation (LES) turbulence model with subgrid turbulent kinetic energy closure. Combustion was modeled using a strained laminar flamelet library approach. Radiative heat transfer was accounted for with a model utilizing the gray-gas approximation. In this study, additional validation analysis is performed using the area validation metric (AVM). These activities are done on multiple datasets involving different variables and temporal/spatial ranges and intervals. The results provide insight into the use of the area validation metric on such temporally varying datasets and the importance of physics-aware use of the metric for proper analysis.

Modeling, analysis and forecasting of the Jordan’s transportation sector energy consumption using artificial neural networks

Modeling, analysis and forecasting of the Jordan’s transportation sector energy consumption using artificial neural networks

Going resilient with digital transformation, human capabilities and innovation readiness: empirical evidence from the energy sector

PurposeThe present study investigated organizational resilience (OR) in the United Arab Emirates (UAE’s) energy sector to identify impactful technological and human variables and assess the hermeneutic effect of digital transformation on value co-creation and OR. The study also investigates the mediating role of value co-creation on a few covariates of OR.Design/methodology/approachThe questionnaire was sent out to 311 professionals in the energy sector, all affiliated with governmental organizations, using quota sampling. A total of 206 collated responses corresponding to the tested variables regarding the influences of digital transformation, employee resilience, innovation readiness, cyber resilience and value co-creation on OR were analyzed using structural equation modeling. Accordingly, a model of eight constructs and their 27 indicators was tested.FindingsInstituting flexibility and adaptability to technological advancements, as well as cyber resilience, was found to enhance digital transformation. The sense of self-efficacy of the professionals who participated in the study led them to develop innovation readiness and thus embrace creativity and encourage co-creation while maintaining collaborative efforts with customers and stakeholders. This mediated several technological and human variables, such as the importance of managers' understanding of customer needs, preferences and pain points, which involves actively seeking and valuing customer feedback to inform decision-making.Practical implicationsWhen iterative prototyping, continuous learning, and OR are integrated into an organization’s culture, they create a robust foundation for a customer-centric mindset. This mindset becomes ingrained in how employees approach their work and make purposeful decisions.Originality/valueThe present study drew empirical insights into OR in the UAE’s energy sector from a resource-based theory perspective. By identifying potential vulnerabilities and implementing appropriate mitigation measures, organizations can reduce the likelihood and impact of disruptions, which can ultimately help them maintain customer satisfaction and loyalty.

Free-standing arrays of BaTiO3 nanotubes for non-enzymatic glucose sensing & hydrophobic coating applications

BaTiO3 nanostructures have been considered as a promising candidates in recent past for energy and biomedical sectors owing to their excellent physiochemical properties, such as high dielectric constant, excellent piezoelectric property, good biocompatibility, non-linear optical characteristics etc. Present study reveals on free-standing arrays of BaTiO3 nanostructures, were fabricated by hydrothermal conversion of anodic TiO2 nanotubes. Morphological and structural information of the BaTiO3 nanotubes were done using FESEM and XRD studies. FESEM analysis revealed that the fabricated samples were having tubular morphology of average length and pore diameter of 4.63 μm and 290 nm respectively. Cubical perovskite crystalline phase of BaTiO3 was confirmed through XRD analysis. The BaTiO3 nanotube samples had shown a higher sensitivity of 44.43 μA mM−1 cm−2 and a faster response of 0.1 s for glucose detection. The fabricated BaTiO3 nanotubes film also showed a higher contact angle of 122.70°. Therefore, our present fabrication on Titanium foil study emphasizes on arrays of BaTiO3 nanotubes which will open up a new window in the development of various types of sensing and hydrophobic coating applications.

Status of Biogas Programmes in India

The study makes an attempt to enquire into the strengths and weaknesses in implementing the programme. Another relevance of the study is that biogas programme is popularly believed to have deeply influenced energy and agricultural sectors. This study provided an opportunity to verify the basis of such popular notion. Looking at biogas programme as an activity of local change, the study makes an effort to find out the options of replicability and scaling up of the biogas programme. It is hoped that the study will bring forth useful clues that can go a long way in improving agriculture in Kerala, especially in the highranges of Kerala.

Gaining insight into lithium-ion battery degradation by a calorimetric approach

With the growing demand for lithium-ion batteries (LIBs) in transportation and renewable energy sectors, ensuring reliability and mitigating degradation are crucial challenges for their widespread deployment. This study investigates the relationship between thermal characteristics and degradation/reliability by developing an in-situ heat measurement methodology for LIBs operating under grid services. Using adiabatic mode-based calorimetry, we determine the thermal behavior of two commercial cells with distinct cathode chemistries (Ni-rich layered oxide and olivine) before and after two years of peak shaving operation and demonstrate a strong correlation between thermal characteristics and electrochemical performance and its degradation. By further analyzing the heat sources separation and differentiating between irreversible and reversible heat, we disclose the underlying degradation mechanisms of LIBs. These findings emphasize the critical role of thermal characteristics in determining LIB reliability and degradation, while the obtained heat data can aid in the development and calibration of LIB state-of-health models for grid applications.

The Impact of Climate Change on Work: Lessons for Developing Countries

Abstract We identify five areas where climate change may impact work and draw lessons for developing countries by reviewing the evidence. Firstly, demand for labor is unevenly affected, with agriculture, heat-exposed manufacturing, and the brown energy sector experiencing downturns, while other sectors may see a rise, resulting in an uncertain overall impact. Secondly, climate change impacts labor supply through absenteeism, shirking, and altering work-time patterns, depending on the activity and sector. Thirdly, productivity may decline, especially in heat-exposed industries, primarily due to health reasons. Fourthly, heightened earnings variability likely increases vulnerability among the self-employed. Fifthly, climate change can influence labor allocation and catalyze sectoral reallocation. Higher temperatures are also linked to increased migration. But caution is needed in interpreting these findings, as studies across these topics predominantly use fixed effect estimation and concentrate on short-term impacts, neglecting adaptation. Emerging research on adaptation indicates that workplace cooling is unappealing for firms with narrow profit margins, while coping strategies of farms and households have unclear optimality due to adoption barriers. Government responses remain understudied, with six potential areas identified: green jobs, green skills, labor-oriented adaptation, flexible work regulation, labor market integration, and social protection. We conclude by outlining future research directions.

Restructuring reforms for green growth

AbstractPolicymakers across the world are striving to tackle the century‐defining challenge of climate change without undermining potential growth. This paper examines the impact of structural reforms in the energy sector (electricity and gas) on environmental outcomes and green growth indicators in a panel of 25 advanced economies during the period 1970–2020. We obtain striking results. First, while structural reforms so far failed in reducing greenhouse gas emissions per capita, there is some evidence for greater effectiveness in lowering emissions per unit of GDP. Second, although energy reforms are not associated with higher supply of renewable energy as a share of total energy supply, they appear to stimulate a sustained increase in environmental inventions and patents per capita over the medium term. We also find strong evidence of nonlinear effects, with market‐friendly energy reforms leading to better environmental outcomes and green growth in countries with stronger environmental regulations. Looking forward, therefore, structural reforms should be designed not just for market efficiency but also for green growth.

Financial Performance and Total Resources: Trend and sensitivity Analysis of Indian Oil Exploration and Production Companies

The firms involved in the exploration and production (E&P) of natural gas resources and crude oil play a crucial role in the energy sector and contribute to the economy. Exploration and production refer to discovering, drilling, and extracting natural gas resources and crude oil from beneath the earth’s surface. Exploration and production firms provide a base for the downstream companies to make crude oil consumable. The financial performance of the downstream companies depends on the cost efficiency of the E&P firms. The purpose of the study is to determine the relationship between the total resources and measures of financial performance. The study is based on secondary data and financial ratios, index numbers applied to get the financial performance, and variability of financial performance. Correlation is used to get the trend and quick impact of variability on the total assets on the financial measures in the short and long run. The study found that while return on total resources is positively influenced in the long run, profitability based on sales and short-term paying ability is negatively governed by the absolute quantity of expansion of all available resources. Although the long-term association is positive, there is a short-term lag in the positive increase of the total resources on the ROA. Overall, based on their average absolute amount of total resources, relatively, the mutual study of the mean growth rate of all resources and financial indicators of Indian E&P explore negativity.