Boundary spanner closeness to partner firm as relational governance in turbulent versus stable environments

Purpose This study aims to explore the overall relationship between a boundary spanner and a partner firm, i.e. boundary spanner closeness to partner firm. Drawing on consumer-service provider relationship literature and the tripartite model of affect-behavior-cognition, the authors identify three key dimensions of such closeness, namely, boundary spanners’ relational ties, customer-specific capabilities and accommodative behaviors, and examine their effects on exchange outcomes in turbulent versus stable environments. Design/methodology/approach The paper examines the effects of three dimensions of boundary spanner closeness on various exchange outcomes (i.e. retailers’ cooperation, satisfaction and willingness for investment) using two industries as exemplars, characterized by distinct levels of environmental turbulence – the retailing networks of a major cell phone company and a petroleum company in China. Findings The results indicate that the three dimensions individually and jointly affect exchange outcomes and the interplay of customer-specific capabilities and relational ties affect exchange outcomes differently across industry turbulence. Originality/value The existing literature lacks a comprehensive understanding of the function of boundary spanners, which serve as a key relational interorganizational governance component. By identifying three key dimensions of boundary spanner closeness and examining their effectiveness in promoting exchange outcomes, this study advances the understanding of the role of boundary spanners in interorganizational governance.

Petroleum Development Oman Forecasting Management System

Production performance forecasting is considered as one of the most challenging and time consuming tasks in petroleum engineering disciplines, it has important implications on decision-making, planning production and processing of facilities. In Petroleum Development Oman (PDO), which is the major petroleum company in Oman, production forecast provides a technical input basis for the economic decisions throughout the exploration and production lifecycle. Reservoir engineers spend more than 250 days per year to complete this process. PDO Forecast Management System (FMS) was introduced to transform the conventional forecasting of gas production. Employing the latest state-of-the-art technologies in the field of data management and machine learning (ML), PDO FMS aims at optimizing and automating the process of capturing, reporting, and predicting hydrocarbon production. This new system covers the full forecast processes including long and short-term forecasting for gas, condensate, and water production. As a pilot project, PDO FMS was deployed on a cluster of 272 wells and relied on agile project management approach to realize the benefits during the development phase. Deployment of the new system resulted in a significant reduction of the forecasting time, optimization of manpower and forecasting accuracy.

Self-perceived knowledge level of epidemic management in medical residents prior to the start of the COVID-19 pandemic in Mexico

Introduction: COVID-19 was declared a pandemic in March 2020, requiring a comprehensive response from all healthcare systems, including Mexico’s. As medical residents’ training did not involve epidemic response, we decided to evaluate their level of training on this subject, specifically self-perceived knowledge level and capacity to respond to epidemiological crises. Methodology: Medical residents from two hospitals belonging to PEMEX (Mexico’s state-owned petroleum company) were included in a cross-sectional study. All participants answered a modified version of the survey developed by the University of Lovaina’s Center for Research and Education in Emergency Care. Participants were analyzed according to their relevant “clinical” or “surgical” residency tracks. Data were analyzed using through Chi-square tests, t-tests, Mann–Whitney U tests, Kruskal-Wallis tests, and Pearson and Spearman correlation coefficients with significance established at p < 0.05. Results: Of a total of 94 resident participants in this study, 56.7% self-perceived themselves as being poorly prepared to confront the pandemic. Only 25.5% of the participants referred previous experience in medical responses to public health emergencies, and only 35.1% reported ever receiving education on this topic. Conclusions: Medical residents—who have been involved with caring for victims of the pandemic—are under the general perception that they are not prepared, experienced, or educated enough to respond to such a widespread massive public health emergency.

Assessment of the effectiveness of corrective maintenance of an oil pump using the proportional intensity model (PIM)

PurposeComplex repairable systems (CRSs) are generally modeled by stochastic processes called “point processes.” These are generally summed up in the nonhomogeneous Poisson process (NHPP) and the renewal process (RP), which represent the minimum and maximum repair, respectively. However, the industrial environment affects systems in some way. This is why the main objective of this work is to model the CRS with a concept reflecting the real state of the system by incorporating an indicator in the form of covariate. This type of model, known as the proportional intensity model (PIM), will be analyzed with simulated failure data to understand the behavior of the failure process, and then it will be tested for real data from a petroleum company to evaluate the effectiveness of corrective actions carried out.Design/methodology/approachTo solve the partial repair modeling problem, the PIM was used by introducing, on the basis of the NHPP model, a multiplicative scaling factor, which reflects the degree of efficiency after each maintenance action. Several values of this multiplicative factor will be considered to generate data. Then, based on the reliability and maintenance history of 12-year pump's operation obtained from the SONATRACH Company (south industrial center (CIS), Hassi Messaoud, Algeria), the performance of the PIM will be judged and compared with the model of NHPP and RP in order to demonstrate its flexibility in modeling CRS. Using the maximum likelihood approach and relying on the Matlab software, the best fitting model should have the largest likelihood value.FindingsThe use of the PIM allows a better understanding of the physical situation of the system by allowing easy modeling to apply in practice. This is expressed by the value which, in this case, represents an improvement in the behavior of the system provided by a good quality of the corrective maintenance performed. This result is based on the hypothesis that modeling with the PIM can provide more clarification on the behavior of the system. It can indicate the effectiveness of the maintenance crew and guide managers to confirm or revise their maintenance policy.Originality/valueThe work intends to reflect the real situation in which the system operates. The originality of the work is to allow the consideration of covariates influencing the behavior of the system during its lifetime. The authors focused on modeling the degree of repair after each corrective maintenance performed on an oil pump. Since PIM does not require a specific reliability distribution to apply it, it allows a wide range of applications in the various industrial environments. Given the importance of this study, the PIM can be generalized for more covariates and working conditions.

Effect of COVID-19 on Dupont based financial performance of three Nationalized Petroleum Companies in India

: Every company has two major objectives in terms of profitability. i.e. Profit Maximization and Shareholders’ Wealth Maximization. Ratio analysis is a good tool which fosters the utilization of company figures to make proper investment decision for various classes of investors and management for taking right decisions at right time. ROE (Return on Equity) comes into the picture in terms of measuring the wealth maximization. It is basically a composition of ROCE or Return on Capital Employed. American paint manufacturing company named DuPont invented DuPont model of ROE analysis. It basically talks about the key factors contributing the return on equity. It can be used to analyze the return in any industry. In this study, we studied the impact of COVID-19 pandemic in their financial performance using DuPont analysis of the three Nationalized Petroleum company including BPCL, HPCL & Indian Oil Corporation.

The Risk Analysis and Modeling of Byco Petroleum in Pakistan Using Extreme Value Theory

The extreme value theory (EVT) has been used to model and measure the distribution of extreme minima of Byco Petroleum in the Pakistan stock market over the period from 2005 to 2012. This paper covers the investigation of distributions that are mostly used in finance including the generalized extreme value (GEV), generalized logistics (GL), and generalized Pareto (GPA) distribution. L-moment ratio diagram is being used to find the appropriate distributions among the distributions. L-moment diagram depicts that GEV and GL distributions are suitable to represent the extremes of Byco Petroleum Pakistan Limited. Thereafter, the probability weighted moment (PWM) method has been used in order to estimate the parameters of probability distributions. Furthermore, Anderson–Darling (AD) goodness-of-fit test is employed to test the goodness of fit among GEV and GL distributions, and it is clear from the results that the GL distribution is more reliable and applicable for extreme minima of Byco Petroleum Company in the Pakistan stock exchange market. EVT and traditional methods are used for value-at-risk (VaR) analysis. The analysis indicates that EVT methods are more suitable for risk measurement in comparison with traditional methods.

Shipping pattern may be altered according to available refining capacity

Alternate optimal solutions in the mathematical programming solution of a real-world problem are rare, unless there are multiple objective functions. In a recent application of 2 mathematical programming solvers to a problem of crude oil logistics, I obtained 2 different optimal solutions. The almost optimal solutions obtained from the convex combinations of the 2 optimal solutions, are feasible as real transportation choices, if the optimal solutions cannot be implemented. It was observed that the 2 solutions led to different capacity utilization at the refineries downstream, and so do the many solution alternatives. This is useful information for the petroleum company during downtime for maintenance or capacity expansion.

Development and Execution of Heritage Petroleum Company Limited’s First Offshore Workover Campaign - A Case History of Successful Implementation of Performance Management

Heritage Petroleum Company Limited (HPCL) is the newest operating oil and gas company in Trinidad and Tobago and was vested and entrusted with the operation and management of all the exploration and production assets of Petroleum Company of Trinidad and Tobago Limited ("Petrotrin"). Being driven by oil-based revenue meant that rig intervention projects had to be innovative, economically viable and practical to meet the company’s financial commitments. This paper presents the concepts and processes behind the development and implementation of HPCL’s Workover Scoping and Procurement Framework. The offshore team recognized the need to frame the well review and workover candidate selection process as well as a procurement process that was both operationally accommodating and in accordance with public procurement regulations. This process would also have to be tested, since it was a new concept that was not practiced by Petrotrin. The well review process involved defining reservoir deliverability and in-place volumes through static and dynamic modelling, establishing current well potential and deliverability via nodal analysis with installed completion designs, topside infrastructure conditions and flow restrictions. The procurement process was achieved by identifying local resources and generating framework agreements for services and equipment. Job specific resources were tendered to ensure a transparent selection and award. The process also involved ranking the risks of all candidates. Economic analyses were performed to determine whether the financial indicators were positive to ensure viability of the campaign. A scorpion plot was also used to manage the performance of this framework during the campaign. The result was a campaign consisting of 15 wells that was delivered on time and within the workover budget. Actual production gain was over 1700 BOPD as opposed to the expected gain of 1450 BOPD. Budgeted Net Present Value (NPV) and actual NPV was calculated to be US$ 9.42 million dollars and US$ 11.7 million dollars respectively. All resources were demobilized and removed from the offshore acreage to reduce risks and floating expense to the company at the end of the campaign.

Applying Front End Loading FEL Approach to Rationalizing Heritage Petroleum Company Limited Forward Development Strategy

This paper presents the methodology used by the Offshore Business Unit of Heritage Petroleum Company Limited (HPCL), to reorganize its future development portfolio. This methodology enabled us to re-organize and rank future projects in order of 1) Developability, 2) Subsurface, Drilling, Flow Assurance and HSSE risks, 3) Financial indicators such as CAPEX and $/BOE, as an approach to maximizing return on investment whilst maintaining the stated goals of the company of monetizing our oil reserves and resources. Following the incorporation of HPCL, the organization attempted to embark on a production stabilization and growth strategy but faced challenges regarding financial and human resource allocation as well as understanding project development best suited for the mature 70 year kit it currently operates. There was a sizable Forward Drilling Campaign (FDP) that remained to be executed from the Legacy company, but there was a need to determine how best to proceed with it. The question was how can we optimize this FDP to attain Heritage’s goals in the short and near term. The answer resided in holding a Pre-Appraisal workshop. A Pre-Appraise Level-1 workshop was held analyzing risk and uncertainty for all future drilling projects. Key to understanding and quantifying inherent risks and opportunities was the presence of a full multidisciplinary team, which included subsurface, facilities, drilling, finance, planning and HSSE personnel. This approach yielded a list of future opportunities that best fit HPCL’s debt-to-capital ratio or debt service coverage position. It also helped to identify projects better suited for joint venture or external capital expenditure options. This workshop resulted in upper management having clear line-of sight regarding the project portfolio, and resource assignment. Once the projects were ranked and grouped, the process of calculating the associated investment to capitalize production across the entire lifecycle was undertaken. A matrix showing Dollar/BOE vs. Project Risk was then built for the new growth strategy. This tool allowed HPCL to select those opportunities that required minimum investment coupled with low HSSE risks. The Pre-Appraise Level-1 workshop guided HPCL to initiate the Shallow Forest Main Field re-development and the East Field drilling development projects as developments to undertake with least risk. The Main Field Shallow Forest Development requires the lowest CAPEX (Drilling and Facilities) and is capital efficient. The proved to non-proven reserves ratio is small (0.05) indicating a high developable remaining resource which will be accessible through secondary or tertiary methods. This approach to understanding development portfolios is new within HPCL; although it has been tried and tested by many operators worldwide when reviewing their capital projects. The Shallow Forest Main Field development carries a low risk profile and is being managed using the Capital Value Process. This project is now in the appraise stage.

The impact of measuring driver performance on the bulk fuel supply chain

Background: The distribution of bulk fuel products to customers is one of the key activities in the downstream petroleum supply chain. For this activity to be effected successfully, three groups of supply chain participants, drivers, supervisors and customers, play key roles. Truck drivers are responsible for conveying the final product to the customer, whilst supervisors ensure that trucks are dispatched on time, driver performance is monitored and performance feedback is properly communicated to drivers. Customers, who purchase the final products, are the foundation of business success. Business success is only possible by meeting or exceeding customer expectations, and it is therefore imperative that the performance of employees is measured and monitored regularly.Objectives: This study was undertaken to determine the impact of measuring driver performance on the bulk fuel supply chain and on customer service.Method: A quantitative research methodology was conducted using structured questionnaires which were disseminated before and after the key performance indicators were implemented to three target groups.Results: The study found that the performance of drivers improved because of the performance feedback they received from supervisors who were perceived to have improved in their performance through the effective utilisation of key performance indicators, and as a result, this increased customer service levels.Conclusion: Whilst the research was limited to a single petroleum company, the results can provide management with guidance and insight on how to improve performance of employees through the use of key performance indicators, with a goal of providing excellent customer service.