Engineering Management Research

Abstract This study addresses a gap in enterprise risk management related to project team performance. Poorly functioning teams may severely erode project net present value (NPV). The erosion of project NPV can be quantified in terms of probability of success (POS). In the oil business POS is based on success criteria for likelihood that exploration efforts for oil & gas prospects will realize the EMV for those assets. Similarly, POS in team work and negotiations is based on success criteria for the likelihood that cooperation between team individuals will be able to deliver the maximum value for the project. Practical rules are formulated to support teams and team leaders in their efforts to optimize the alignment of team members in order to enhance the team's effectiveness. The probability of success (POS) is split into three fundamental factors of alignment: P Culture , P Skills and P Goals . The dynamic effect of team learning on team alignment is graphed as the Cumulative POS. The cost of failure is graphed for a range of POS values, and visualizes the impact on the EMV of extra Team OPEX, each normalized by the project NPV. Applications are possible in all kinds of functional teams, including change management teams that need to build coalitions to effectuate lasting change. The interaction between members of engineering and other professional teams has been studied intensively, but the expression of team performance in numbers as quantified here is a new direction

Can we close Earth's sustainability gap?

a b s t r a c t The principal options for engineering Earth's ecological future can be concisely visualized in a conceptual dilemma matrix. Scaling of the matrix with real world data confirms the widening of Earth's sustainability gap, due to our increasing ecological footprint. The simplicity of the dilemma matrix articulated here may help to focus the debate at future Global Summits and World Future Energy Summits on the critical scenario options. Geoscientists and engineers at energy companies share a major responsibility with many societal actors in setting the right example, particularly in searching for sustainable energy solutions. One view is that technology can help solve all issues. Another view is that nature is needed for sustainable ecosystem services. A most pessimistic view is based on analogy of human behavior with that of ants -eusocial groups like ourselves. Ant wars for access to limited resources warn us for a future where scarcity of resources may force us to resort to brutal, competitive behavior -rather than civilized diplomacy. Options to avoid such an outcome are outlined in this study

Gaussian Decline Curve Analysis of Hydraulically Fractured Wells in Shale Plays: Examples from HFTS-1 (Hydraulic Fracture Test Site-1, Midland Basin, West Texas)

The present study shows how new Gaussian solutions of the pressure diffusion equation can be applied to model the pressure depletion of reservoirs produced with hydraulically multi-fractured well systems. Three practical application modes are discussed: (1) Gaussian decline curve analysis (DCA), (2) Gaussian pressure-transient analysis (PTA) and (3) Gaussian reservoir models (GRMs). The Gaussian DCA is a new history matching tool for production forecasting, which uses only one matching parameter and therefore is more practical than hyperbolic DCA methods. The Gaussian DCA was compared with the traditional Arps DCA through production analysis of 11 wells in the Wolfcamp Formation at Hydraulic Fracture Test Site-1 (HFTS-1). The hydraulic diffusivity of the reservoir region drained by the well system can be accurately estimated based on Gaussian DCA matches. Next, Gaussian PTA was used to infer the variation in effective fracture half-length of the hydraulic fractures in the HFTS-1 wells. Also included in this study is a brief example of how the full GRM solution can accurately track the fluid flow-paths in a reservoir and predict the consequent production rates of hydraulically fractured well systems. The GRM can model reservoir depletion and the associated well rates for single parent wells as well as for arrays of multiple parent–parent and parent–child wells

Production Forecasting of Unruly Geoenergy Extraction Wells Using Gaussian Decline Curve Analysis

Fast and rigorous well performance evaluation is made possible by new solutions of the pressure diffusion equation. The derived Gaussian pressure transient (GPT) solutions can be practically formulated as a decline curve analysis (DCA) equation for history matching of historic well rates to then forecast the future well performance and estimate the remaining reserves. Application in rate transient analysis (RTA) mode is also possible to estimate fracture half-lengths. Because GPT solutions are physics-based, these can be used for production forecasting as well as in reservoir simulation mode (by computing the spatial and temporal pressure gradients everywhere in the reservoir section drained by either an existing or a planned well). The present paper focuses on the physics-based production forecasting of so-called “unruly” wells, which at first seem to have production behavior noncompliant with any DCA curve. Four shale wells (one from the Utica, Ohio; one from the Eagle Ford Formation, East Texas; and two from the Wolfcamp Formation, West Texas) are analyzed in detail. Physics-based adjustments are made to the Gaussian DCA history matching process, showing how the production rate of these wells is fully compliant with the rate implied by the hydraulic diffusivity of the reservoir sections where these wells drain from

Accelerating the three Dimensions of E&P Clockspeed e A novel strategy for optimizing Utility in the oil & gas industry

a b s t r a c t As the global Oil & Gas Industry enters its third, late lifecycle stage (outlined in the introduction of this study), new strategies and conceptual tools are needed to postpone -or reverse -the decline of the E&P industry. The problem is this: the late lifecycle is principally heralded by limited supply due to finite hydrocarbon reserves, while energy demand soars as world population and the global economy continue to grow. This study therefore proposes a framework through which an E&P company can critically assess its capability in accelerating lag-time between exploration and production. In the first part of this paper (Sections 1-3), the need for a phase-shift toward faster clockspeeds for the Oil & Gas industry is argued to be an important step to close the energy supply gap. In the second part of this paper (Sections 4-6), the strategy concept of clockspeed acceleration is further elaborated and optimization methods for the three principal dimensions of E&P clockspeed acceleration are discussed. The three Clockspeed Accelerators TM are: workflow speed, improvement rate of Uncertainty Mitigation and accrual speed of portfolio value. The third part of this paper (Sections 7-11) presents the empirical analysis of E&P clockspeed performance for two peer groups (IOC supermajors and public private partnership NOCs) comprising six companies each. The acceleration of E&P clockspeed can help to optimize production levels of conventional and unconventional oil, and includes diversification strategies that replace non-renewables with renewables. In summary, E&P Clockspeed Accelerators provide the gearshift instruments that enable the energy industry to better meet the required demand/supply ratios. The results of this study translate into the following deliverables for practical use by Oil & Gas professionals: -insight into the concept of clockspeed in E&P industry setting, -use of Clockspeed Accelerators TM as gearshift lever tools for monitoring and directing E&P clockspeed, -a template for benchmarking and scaling the cardinal axes of E&P Clockspeed Accelerators TM for companies in time-series analysis and cross-sectional analysis, -insight in the critical drivers of E&P clockspeed acceleration based on the companies studied, -a set of recommendations to support and speed up the optimization of the individual Clockspeed Accelerators TM for Oil & Gas companies

Balancing Venturi and Laissez-Faire Management Styles: Insights from Fluid Mechanical Analogs

Mobilizing distributed Organizational Intelligence involves managerial efforts whereby the generation of new tacit knowledge requires dissemination of newly codified externalized knowledge. The managerial role in the early stage of knowledge creation is to support and stimulate the process of knowledge generation and to aid the diffusion of knowledge across organizational boundaries. In contrast, the subsequent 'harvesting' and goal-oriented application of knowledge requires convergence of human actors (H) as carriers of distributed intelligence (DI). Optimization of the organizational performance and improved workflow efficiency is best effectuated by applying insights from fluid mechanical analogs. Several such analogs are introduced here and these provide insight that helps to funnel tacit and explicit knowledge into tangible asset value. Three sets of managerial lessons are inferred from the analogs: (1) Social bonding between professionals needs to be stimulated because professionals with strong social bonds (S) can sustain effective workflows under relatively high pressures, while weak social bonds lead to turbulence and disruption; (2) Effective vision sharing is essential for goal-oriented and accelerated knowledge development in DI systems, and; (3) Managerial pressure may not overheat the critical limit that can be handled by resilient and strongly bonded DI networks, as this would result in disruptive turbulence even in experienced neural networks

Diffusive Mass Transfer and Gaussian Pressure Transient Solutions for Porous Media

This study revisits the mathematical equations for diffusive mass transport in 1D, 2D and 3D space and highlights a widespread misconception about the meaning of the regular and cumulative probability of random-walk solutions for diffusive mass transport. Next, the regular probability solution for molecular diffusion is applied to pressure diffusion in porous media. The pressure drop (by fluid extraction) or increase (by fluid injection) due to the production system may start with a simple pressure step function. The pressure perturbation imposed by the step function (representing the engineering intervention) will instantaneously diffuse into the reservoir at a rate that is controlled by the hydraulic diffusivity. Traditionally, the advance of the pressure transient in porous media such as geological reservoirs is modeled by two distinct approaches: (1) scalar equations for well performance testing that do not attempt to solve for the spatial change or the position of the pressure transient without reference to a well rate; (2) advanced reservoir models based on numerical solution methods. The Gaussian pressure transient solution method presented in this study can compute the spatial pressure depletion in the reservoir at arbitrary times and is based on analytical expressions that give spatial resolution without gridding-meaning solutions that have infinite resolution. The Gaussian solution is efficient for quantifying the advance of the pressure transient and associated pressure depletion around single wells, multiple wells and hydraulic fractures. This work lays the basis for the development of advanced reservoir simulations based on the superposition of analytical pressure transient solutions

Optimization of Fracture Spacing and Well Spacing in Utica Shale Play Using Fast Analytical Flow-Cell Model (FCM) Calibrated with Numerical Reservoir Simulator

Recently, a flow-cell model (FCM) was specifically developed to quickly generate physics-based forecasts of production rates and estimated ultimate resources (EURs) for infill wells, as the basis for the estimation of proven undeveloped reserves. Such reserves estimations provide operators with key collateral for further field development with reserves-based loans. FCM has been verified in previous studies to accurately forecast production rates and EURs for both black oil and dry gas wells. This study aims to expand the application range of FCM to predict the production performance and EURs of wells planned in undeveloped acreage of the wet gas window. Forecasts of the well rates and EURs with FCM are compared with the performance predictions generated with an integrated reservoir simulator for multi-fractured wells, using detailed field data from the Utica Field Experiment. Results of FCM, with adjustment factors to account for wet gas compressibility effects, match closely with the numerical performance forecasts. The advantage of FCM is that it can run on a fast spreadsheet template. Once calibrated for wet gas wells by a numerical reservoir simulator accounting for compositional flow, FCM can forecast the performance of future wells when completion design parameters, such as fracture spacing and well spacing, are changed