In the Big Data age, businesses in every industry must deal with vast volumes of data. Several experts and practitioners have lately emphasized the need of understanding how, why, and when Big Data Analytics (BDA) applications may be a valuable resource for businesses seeking a competitive edge. However, BDA pays off for some firms while failing to pay off for others due to the fact that investment in Big Data continues to present significant challenges due to the missing link between analytics capabilities and firm performance. According to a recent survey, many businesses spend the bulk of their time analyzing data, with only a tiny fraction employing Big Data Analytics to forecast outcomes and even fewer utilizing analytics apps to enhance processes and strategies. As a result, BDA is not widely used, and only a few companies have seen any benefit from it. To address this issue in the telecommunications domain and in light of the paucity of research on the subject, this study focused on the BDA Pillars (BDAP) in order to achieve benefits through increased revenues and cost savings. For the purpose of this research we have adopted qualitative approach with case study method, and technique of data collection includes semi-structure interview and document analysis. The Delphi technique and in-depth interviews conducted confirmed the existence of five critical elements that contribute to the sustainability of BDAPs and their impact on firm performance.

In the path to a net-zero carbon and energy transition from fossil fuel, the world is facing a dilemma of growing global energy demand and required actions on climate-related risks. While over 80% of the current global energy needs are supplied by fossil fuels, the number of carbon capture, utilization and storage (CCUS) projects is limited in this sector. There is a huge gap between the scale and distribution of ongoing CCUS projects and the carbon intensity (CI) of energy-intensive industries. Furthermore, the climate impact of growing reliance on unconventional resources (Tar sands and shales) as well as the depletion of conventional resources poses challenges to the oil and gas sector to meet energy demand, while limiting their greenhouse gas (GHG) emissions. On the other hand, the economic viability of CCUS projects is highly sensitive to carbon credits policies, which are not yet fully integrated in a way to fill the current gap in the number, scale and distribution of these projects. Moreover, there is limited consistency between the allocated decarbonization funds and the anticipated economic growth of fossil fuel economies to promote wide-scale global resilience to carbon exposure. Therefore, it is essential to take climate-related risks, including socioeconomic impacts, into consideration for the decision-making process of companies and governments to embrace low-carbon energy. The focus of this article is on carbon resilience calibration and emissions scenario analysis in investment decisions to realize decarbonization goals through balancing short-term actions with long-term energy transition plans. The challenges and prospects of the application of CCUS technologies as an industrial decarbonization approach are discussed. Carbon footprint (CFP) observing, factoring and reporting workflows for correlating carbon exposure and resilience as part of climate assessment are introduced. Moreover, the main elements of carbon resilience scenarios are analyzed to fill the gap between the current industrial activities and decarbonization plans and to avoid making decisions solely based on economic aspects. Finally, we propose a workflow for carbon resilience calibration and a cash flow model for a sample CCUS project in the upstream oil and gas industry.

On the path to achieving net‐zero emissions targets by 2050 and meeting the increasing electricity demand, investigations on the carbon intensity of electricity is of interest as an important decision‐making parameter in decarbonizing the power sector and replacing nonrenewable power plants in regions of low rainfall and limited water resources to enhance the transparency of policies toward net‐zero transition. In this context, the potential of solar photovoltaics (PV) has been highlighted in recent years due to their low‐emission intensity compared to other renewable sources, highly regarded economic prospects, and unprecedented global growth of installations. Considering Iran's power crisis in terms of the mismatch between production and consumption and a worsening of the environment due to high‐carbon power, this paper presents the assessment of the environmental and economic viability of a 10 MW on‐grid solar PV plant to improve energy security and sustainability. First, the carbon intensity (CI) and levelized cost of energy (LCOE) of electricity generated in the power industry in Iran in comparison with the global status is discussed. Then, the environmental aspects of different types of PV inverter modulus and panels are assessed by utilizing the life cycle assessment approach, to select the optimum design in terms of CI. Finally, the economic scenarios are analyzed in terms of LCOE and the sensitivity analysis on the availability factor. The combined environmental‐economic assessment results of the case solar power plant with CI of 63.9 tCO₂/GWh and LCOE of 11 $/MWh offers deep insights into the financial and environmental performance of solar PVs in the country's sustainable development roadmap and highlights the importance of regulatory policies, absorbing green climate funds, and investment in the expansion of solar systems to enable the decarbonization of electricity as an important measure for sustainable development.

As a result of reduction trend in exploration of super-giant carbonate fields and depletion of the proven mature fields categorized as easy oil, development of tight, deep carbonates with more complexities in reservoir rock and fluid behavior have become of interest for exploration and development companies in recent years. New challenges have arisen in development of complex carbonates due to fracture network distribution uncertainty, lateral and vertical fluid behavior heterogeneities, unstable asphaltene content, high H2S and CO2 contents and high salinity formation brine. The complexity elements and problems for downhole sampling have made the full understanding of the reservoir behavior and consequently availability of data for further routine analysis and utilization of simulation model as the main way of data integration limited. Therefore, there is an emerging need to better understand the challenges surrounding production and enhanced oil recovery strategies in these reservoirs for an improved oil recovery decision making system. In this paper, the challenges in production, stimulation and enhanced oil recovery strategies in newly developed complex carbonates are addressed and analyzed based on the changes to the chemical and mechanical environment. An integrated decision-making workflow based on coupled hydro-mechanical mechanisms in water based EOR methods is discussed.