Resource transparency and energy transition: The role of SEC oil and gas reserve reporting in future energy systems

Guoquan Fan; Mengyue Guo; Yun Wang

doi:10.59400/esc4190

Resource transparency and energy transition: The role of SEC oil and gas reserve reporting in future energy systems

Guoquan Fan
Dagang Oilfield Branch of China National Petroleum Corporation, Tianjin 300280, China
Mengyue Guo
Dagang Oilfield Branch of China National Petroleum Corporation, Tianjin 300280, China
Yun Wang
Dagang Oilfield Branch of China National Petroleum Corporation, Tianjin 300280, China

Article ID: 4190

Keywords: SEC reserve reporting, resource transparency, energy transition, stranded assets, climate-related financial disclosure

Abstract

The world energy paradigm shift is changing the manner in which oil and gas resources are rated, regulated, and reported. The review studies the purpose of the U.S. Securities and Exchange Commission (SEC) oil and gas reserve reporting as one of the main transparency tools of resources and evaluates its applicability in future energy systems. Conventionally, the SEC reserve reporting has minimized information asymmetry in the capital markets through standardization of disclosure of economically viable production of hydrocarbon reserves and therefore, facilitated the protection of investors, asset-pricing, and corporate responsibility. Nonetheless, the article states that the traditional reasoning behind reserve reporting is being more and more questioned by decarbonization, financial risk associated with climate, carbon limits, and shifting capital allocation trends. Even with reported reserves, technical, and commercial producibility may remain, but innovation does not entirely account for transition-related risk conditions like stranded asset risk, fossil entrapment, emissions exposure, and demand decline in low-carbon systems. With a combination of the views of reserve classification, securities regulation, energy governance, and transition finance, this review indicates that SEC reserve reporting is still needed but not sufficient as a standalone transparency measure. The article identifies the necessity to revise the reserve disclosure by incorporating more deeply into climate-related reporting, scenario-based analysis, and better addressing uncertainty. It comes to a conclusion that reserve reporting needs to be redesigned as a fossil asset-centric accounting system into one that is more dispositionally inclusive of transition to control resource value in the decarbonization of energy systems.

Published

2026-05-12

How to Cite

Fan, G., Guo, M., & Wang , Y. (2026). Resource transparency and energy transition: The role of SEC oil and gas reserve reporting in future energy systems. Energy Storage and Conversion, 4(2). https://doi.org/10.59400/esc4190

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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Aluminum zinc oxide (AZO) is a nontoxic and a low-cost material that finds application as a transparent conducting electrode in photovoltaic devices. In this study the (direct current) DC magnetron sputtering of AZO films is carried out at different deposition times of 5, 10, 15, 20 and 25 min’s at room temperature and it’s structural, optical, electrical and morphological properties are studied for its use as a front contact for thin film solar cell application. The structural study suggests that the preferred orientation of grains along (002) plane having hexagonal structure and the optical and the electrical studies suggest that the films show an average transmission of 70% and a resistivity of the order of 10 -4 Ωcm. On the other hand, the scanning electron microscopy (SEM) images suggest the formation of packed grains having a homogeneous surface. Moreover in order to study the optoelectronic properties of prepared samples, the electronic and optical calculations of the AZO are performed by the first-principles calculations using density functional theory (DFT).

Investigation of self-excited induction generator for supporting domestic loads and its extension to a microgrid

This study provides a technical and financial analysis for the incorporation of a microgrid structure with a wind energy conversion system for producing electricity. This study’s primary aim is to provide solutions for issues that arise when isolated induction generators are employed with microgrids. A closed-loop smart electronic load controller is used to regulate the loads in the system that are supplied by the generation. A switched variable capacitor bank is used to supply reactive power initially during a voltage dip at varying winds and loads to sustain the voltage profile. Additionally, a simple voltage control loop-based controller for the generator side converter maintains the voltage at a steady level. Using HOMER software, an economic study of the suggested wind-based microgrid structure is also presented. A laboratory experimental setup is used to support the MATLAB/Simulink study of the proposed method and its control. The findings back the feasibility of implementing the suggested plan in grid-isolated regions for supplying critical loads.

Research progress on ZnO/MoS₂/rGO ternary photocatalysts

Energy shortage and environmental pollution have become one of the important global issues, and semiconductor photocatalytic technology is considered as one of the effective means to solve these problems. As a new and efficient green material, ZnO has attracted wide attention. ZnO is widely used in the field of photocatalysis due to its non-toxicity, low cost, environmental friendliness, adjustable band gap, high electron density, and chemical stability. However, the recombination of photogenerated charge carriers in ZnO hinders its practical application and lowers the utilization efficiency of visible light. On the other hand, molybdenum disulfide/reduced graphene oxide (MoS₂ /rGO), as a binary non-precious metal co-catalyst, has a larger specific surface area, suitable band gap width, and visible light response capability compared to single-phase graphene co-catalyst. Therefore, introducing MoS₂ /rGO co-catalyst into the ZnO system can provide more active sites, reduce the probability of photogenerated charge carrier recombination, and improve the utilization efficiency of visible light. In this review, we summarize the hydrothermal synthesis methods for preparing this highly demanded nanocomposite material, including one-step and stepwise methods. Subsequently, we elaborate on the mechanism of enhancing light absorption and achieving efficient electron-hole separation behavior in the ternary system heterojunction structure during the photocatalytic process. Due to its significant advantages, this ternary system heterojunction structure has been widely applied in the field of photocatalysis, including applications such as pollutant degradation, sterilization, and water splitting.

Wind power forecasting technologies: A review

This study addresses the critical role of wind power forecasting in ensuring stable and reliable power system operations. Wind Power Forecasting is critical for the efficient operation of plant, time scheduling, and it’s balancing of power generation with grid integration systems. Due to its dependency on dynamic climatic conditions and associated factors, accurate wind power forecasting is challenging. The research delves into various aspects, including input data, input selection techniques, data pre-processing, and forecasting methods, with the aim of motivating researchers to design highly efficient online/offline models on weather-based data. The overarching goal is to enhance the reliability and stability of power systems while optimizing energy resource utilization. The analysis reveals that hybrid models offer more accurate results, highlighting their significance in the current era. This study investigates different Wind Power Forecasting (WPF) models from existing literature, focusing on input variables, time horizons, climatic conditions, pre-processing techniques, and sample sizes that affect model accuracy. It covers statistical models like ARMA and ARIMA, along with AI techniques including Deep Learning (DL), Machine Learning (ML), and neural networks, to estimate wind power.

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