University business idea incubation and stakeholders' engagement: closing the gap between theory and practice

PurposeThe paper aims to contributes on the debates about University Idea Incubation by investigating the role and the engagement of different University's stakeholders in the process of opportunity recognition in an entrepreneurship education program targeted at students with an interdisciplinary background.Design/methodology/approachThrough a longitudinal case study methodology, the Contamination Lab at University of Salento (Lecce, Italy), the learning approaches and the knowledge process to create an entrepreneurial awareness, mindset and capability in students with different educational background are presented.FindingsThe findings demonstrates the crucial role of stakeholders' engagement for business idea presentation, open innovation challenge, contamination workshop on specialized topics, enterprise projects are important vehicle for effective students' business ideas and innovative projects development in a multidisciplinary environment. The close interaction among students, academia, companies and institutions creates a favourable environment that enables opportunity identification, idea generation through a deep contamination of knowledge, skills and experiences.Research limitations/implicationsLimitations include the need to generalise the results even if this limitation is typical of the case study methodology. Other research is necessary for an in-depth analysis in deep of the other Contamination Lab in Italy and to derive the “invariance traits” of this environment according to the features of the local entrepreneurial ecosystems.Practical implicationsImplications for practices include recommendations for designing innovative programs where the interactions between University-Institutions-Industry are realized.Originality/valueA conceptual framework is proposed by defining all the entrepreneurial knowledge process and knowledge creation within the Contamination Lab, highlighting the contribution of the stakeholders in each phase and learning initiative of the program.

Recovery Factor Improvement; A Success Story of Improving 10% of RF in Greater Natih Reservoirs, North of Oman

Recovery Factor Improvement (RFI) is a process to check the hydrocarbon production efficiency by incorporating the actual static and dynamic field data, as well as the way how the field being operated. This has been a common process within Shell's portfolio since 2018 (Ref; Muggeridge et al., 2013 & Smalley et al., 2009). The approach has been developed to stimulate the identification of new opportunities to increase the recovery from the existing fields and to aid the maturation of these opportunities into the Opportunity Realization Process. There are four (4) factors that affected overall reservoir recovery factor, they are: Pressure efficiency; related to which pressure can be reduced in the reservoir as dictated by the relevant facilities and wells.Drainage Efficiency; the proportion of the in-place hydrocarbon that is pressure-connected directly to at least one producing well on a production timescale.The "secondary pay" efficiency; takes into account the volumes of poorer quality rock in which the gas remains at pressure above the lowest pressure just outside the wellbore (Pf) when the reservoir is abandoned.Cut-off Efficiency; the proportion of hydrocarbon that is lost due to non-production of the tail.This approach was applied in the dry gas Natih Reservoir fields in the PDO concession area. Before the implementation of RFI, the average recovery factor for Natih was around 70%. This was considered low for a homogenous-dry gas reservoir. The targeted Natih fields were benchmarked against each other with a total of 11 fields with similar reservoir properties. Post the benchmarking exercise, the expected field recovery factor is approximately ~90-93%. The team managed to map out the opportunities to achieve the targeted RF and identified the road map activities. The activities are mainly related to: production optimization: retubing, re-stimulation reduce drainage: infill drilling, horizontal well reduce the field intake through compression The outcome of the mapping was then further analyzed through integrated framework to be matured as a firm-project. The new proposed activities are expected to add around 9% additional recovery to the existing fields. There will be a remaining activities which will be studied in the future, example infill wells and intelligent completions. These will close the gap to TQ and add other addition RF of 11-13%. As conclusion, the RFI was seen as a structured approach to better understanding the field recovery factor based on the integrated surface and subsurface data with a robust analysis to trigger opportunity identification linked to RFI elements. It is similar concept as sweating the asset by generating limit diagram for each recovery mechanism & the road map to achieve the maximum limit. This paper will highlight the Natih Fields RFI analysis, highlighting the key learning and challenges.

Unlocking Opportunities for Gas Lift Well Surveillance - Building the Framework for Consolidated Data Capture and Processing

Gas lift operations are highly dependent on data quality and team competence to operate the asset efficiently. Traditional methods for gas lift well surveillance and diagnostics rely on wireline services, a method with growing constraints to adapt to constantly evolving well and operational challenges. The Well Intervention-less Tracer Surveillance System (WITSS) provides a cost effective, comprehensive approach to well surveillance without the reliance on tools entering the well. This results in reduced HSE risks and no associated deferred production. This paper describes a pilot implementation to evaluate the adequacy and accuracy of this technology in the context of ADNOC Onshore gas lift producers. The objective is to evaluate its performance against conventional method data sets and assess the reproducibility of data where no reference existed. The 10 well pilot included both accessible and obstructed wells. Data from the custom designed modular portable kit used for executing the surveillance activities, was analyzed and compared against conventional flowing gradient surveys with full data consumption in well models for comprehensive nodal analysis and opportunity identification. For this pilot, ten wells were surveyed twice using the WITSS method. Results were compared to traditional methods acquired through wireline surveys for accessible wells, and against established multi-phase flow correlations for obstructed wells. The pilot confirmed the WITSS method is as accurate as conventional gauge measurements in mapping pressure and temperature profiles in gas lifted wells. The WITSS method provided additional insight on accurate gas consumption based on the assessment of total gas lift utilization per well and allowed comprehensive model calibration and well performance definition. It also identified potential integrity issues via identification of primary injection at designed stations and secondary unwanted injection sites. Continuous compositional gas analysis of both injected and produced gas streams provided additional verification for analyzing gas lift injection performance. It also highlighted a change in fluid compositional analysis opening discussions for material selection review of the assets. Production uplift identified from 50% of wells was compliant with the reservoir management strategy. The value proposals of flow stabilization through gas lift valve re-calibrations and replacements, adjustment of injection flow rate and further controls on injection pressure management are under process for implementation. Full field scale up scenario is under preparation.

The novelty-centered business model: a transition mechanism between exploration and exploitation in SMEs

PurposeAs the transition between exploration and exploitation is a unique challenge for SMEs, what mechanism(s) might facilitate this transition? Building on the entrepreneurship literature's entrepreneurial opportunity identification and development framework, this study hypothesizes that the novelty-centered business model (NCBM) may serve as such a mechanism.Design/methodology/approachBased on cross-sectional survey data collected from 169 Italian SMEs in various sectors, this study tests the mediation, moderation and moderated mediation relationships using the statistical PROCESS procedure.FindingsSupporting the hypotheses that exploration and exploitation are positively associated within SMEs, that NCBM mediates this relationship and that the indirect relationship between exploration and exploitation by way of NCBM is stronger for SMEs with employees of medium to high creative human capital, the results suggest that SMEs can more effectively exploit new ideas identified in the exploration phase by developing an NCBM and accessing their creative human capital.Research limitations/implicationsAlthough the robustness checks confirm the direction of the proposed hypotheses, given the cross-sectional nature of the dataset used, a longitudinal study would further validate the proposed framework.Practical implicationsSMEs can successfully achieve the transition between exploration and exploitation by reinventing their business model to compensate for their limited resources in terms of financial or relational capital. They can further enhance their ability to reinvent their business model and, in turn, to exploit innovations by hiring and retaining employees with greater creative human capital.Originality/valueThis study draws on the entrepreneurial opportunity, ambidexterity (exploration-exploitation) and business model literature to enhance our understanding of the role of the NCBM design concept (business model innovation) as a mechanism to achieve temporal ambidexterity in SMEs.

Integrated Brownfield Opportunity Identification Using the Efficiency Factor Approach

The long-term prosperity of oil and gas companies requires a constant influx of new volumes of producible oil and gas that can be developed to replace existing production. Without such activity it is inevitable that production will eventually fall as the resource base is gradually consumed The attractiveness of achieving more barrels from existing discovered fields has always been strong as it has long been recognized that such opportunities can be economically attractive and rapidly brought to fruition. It is also recognized however that such opportunities may be more complex relying both upon excellent subsurface understanding and successful brownfield project execution. It is therefore not surprising that in many cases actual recovery factors (produced volume/initial in-place volume) in oil and gas fields can be significantly less than what should be technically achievable. Identification of economically robust brownfield opportunities remains an industry challenge. In this paper we address this challenge by reporting a new workflow for brownfield opportunity identification leading to recovery factor improvement. Shell's Recovery Factor Improvement (RFI) Workflow was developed to address these issues and builds upon the existing best practice workflows to better explore and define the activities that would be required to achieve top quartile recovery factor performance. The workflow combines elements of various existing published approaches: (1) Shell's TQ-EUR Tool is an internal database that allows current and forecast recovery factor to be compared with that of analogue reservoirs using a reservoir complexity factor and key reservoir performance parameters as comparison criteria across the Shell portfolio. (2) An efficiency factor-based analysis of recovery factor; (3) a structured workshop to elicit new recovery factor improvement activities by addressing each individual efficiency factor in turn; (4) Consistent reporting of results. The combination of these approaches creates a powerful workflow to improve brownfield field opportunity identification and maturation. The RFI Workflow is intended to provide asset teams with a practicable and repeatable process that can be completed without specialist technical support or software to enable the identification of robust new opportunities. Experience with using the new workflow has demonstrated that it is able to bring new understanding to asset teams, consistently identify new opportunities and highlight common portfolio-wide opportunity types that would benefit from further central technology development funding.

A Conceptual System of Antecedents and Processes in Social Entrepreneurship Opportunity Identification

Aiming to complement and ground the theory of social entrepreneurship opportunity identification, we draw from a database of 2,872 entrepreneurs’ life stories with two main objectives. The first is to provide a comprehensive list and categorization of antecedents of opportunity identification in the context of social entrepreneurship. The second is to demonstrate the systemic interconnections between those and build a model of social entrepreneurship opportunity identification. We review the literature and establish a framework of five high-order key antecedents’ areas (context, background, social networks and interactions, affect, and cognitive process). We then proceed to a five-step empirical triangulation methodology mixing computerized and manual content analysis. We thereby identify 42 antecedents nested into 17 first-level items grouped into the five high-order key antecedents’ areas. Our detailed results shed light on a wide array of previously ignored antecedents and provide more precisions about those that had already been documented elsewhere. Finally, we highlight and explain the relationships between the antecedents, show that they constitute an “opportunity growing ground,” and present a full model of social entrepreneurship opportunity identification based on their interconnections. The context of the social entrepreneur combines stable features regarding access to various resources, a strong geographical identity and history, the encounter of several worlds, all condition or are conditioned by his/her social networks and background. This context is also subject to diverse constraints and institutional barriers that can shape the entrepreneur’s background, her/his experiences, as well as his/her affect specificities. This stable context is at some point hit by elements of change that disrupt this stability, triggering chains of reactions between the various antecedents of opportunity identification.

Enhancing Well, Reservoir and Facilities Management WRFM Opportunity Identification with Data Driven Techniques

A key to successful Well, Reservoir and Facilities Management (WRFM) is to have an up-to-date opportunity funnel. In large mature fields, WRFM opportunity identification is heavily dependent on effective exploitation of measured & interpreted data. This paper presents a suite of data driven workflows, collectively called WRFM Opportunity Finder (WOF), that generates ranked list of opportunities across the WRFM opportunity spectrum. The WOF was developed for a mature waterflooded asset with over 500 active wells and over 30 years of production history. The first step included data collection and cleanup using python routines and its integration into an interactive visualization dashboard. The WOF used this data to generate ranked list of following opportunity types: (a) Bean-up/bean-down candidates (b) Watershut-off candidates (c) Add-perf candidates (d) PLT/ILT data gathering candidates, and (e) well stimulation candidates. The WOF algorithms, implemented using python, largely comprised of rule-based workflows with occasional use of machine learning in intermediate steps. In a large mature asset, field/reservoir/well reviews are typically conducted area by area or reservoir by reservoir and is therefore a slow process. It is challenging to have an updated holistic overview of opportunities across the field which can allow prioritization of optimal opportunities. Though the opportunity screening logic may be linked to clear physics-based rules, its maturation is often difficult as it requires processing and integration of large volumes of multi-disciplinary data through laborious manual review processes. The WOF addressed these issues by leveraging data processing algorithms that gathered data directly from databases and applied customized data processing routines. This led to reduction in data preparation and integration time by 90%. The WOF used workflows linked to petroleum engineering principles to arrive at ranked lists of opportunities with a potential to add 1-2% increment in oil production. The integrated visualization dashboard allowed quick and transparent validation of the identified opportunities and their ranking basis using a variety of independent checks. The results from WOF will inform a range of business delivery elements such as workover & data gathering plan, exception-based-surveillance and facilities debottlenecking plan. WOF exploits the best of both worlds - physics-based solutions and data driven techniques. It offers transparent logic which are scalable and replicable to a variety of settings and hence has an edge over pure machine learning approaches. The WOF accelerates identification of low capex/no-capex opportunities using existing data. It promotes maximization of returns on already made investments and hence lends resilience to business in the low oil price environment.

Countrywide Integrated Capacity Model – Enabling Production Planning and Performance Management Leveraging Big Data and Digitization of Engineering Workflows

Production planning and performance management imply diverse challenges, mainly when dealing at corporate level in an integrated operating company. Production forecast considers technical capacities, available capacities, and operationally agreed target capacities. Such complex process may hinder taking advantage of market opportunities at the right time. Proactive scenario management and information visibility across the organization are key for success. This paper intends to share the lessons learned while rolling out a countrywide integrated capacity model solution supporting corporate production planning and performance management. The rollout processes aimed at digitizing the monthly and yearly production forecasting. In addition, these processes shall enable formulating proactive scenarios for avoiding shortfalls, maximizing gas throughput, production ramp up, and minimizing operating cost from existing capacity. Abu Dhabi's Integrated Capacity Model is an integrated production planning and optimization system relying on a large-scale subsurface-to-surface integrated asset model system; in this paper, we focus on the incremental progress of the challenges derived from the various rollout efforts. The rollout of such a complex solution relies on basic tenets for managing the change across a large organization. The first tactic is about continuous stakeholder engagement through value demonstration and capabilities building. Engagement is achieved by continuously providing information about proactive shortfall and opportunity identification within the installed asset capacity. Monthly asset reviews provide the basis for user interaction and initiate the basis for establishing ad-hoc production maximization scenarios. Establishing a data governance and performance metrics were also key for embedding the solution in the business processes. The solution delivers tangible and intangible value. From the tangible point of view, it contributes to production efficiency gains by compensating during specific proactively identified shortfalls and after-the-fact events. As a result, our solution has been instrumental in deriving cost reduction scenarios and profitability gains due to optimum GOR management. In addition, the system use has reported various intangible gains in terms of better data utilization, enhanced corporate database quality and reduced overall human load in managing production capacity. The solution described in the paper implements a simpler way the production planning and performance management at corporate level in a large integrated operating company. The in-house developed tool and its implementation is a novel approach in terms of integration, complexity, and practical application to the fields in Abu Dhabi.