Characterizing Uncertainty In Oil and Gas Evaluations

Caldwell, Robert W.; Heather, D.

doi:10.2523/68592-ms

Cited by 7 publications

(2 citation statements)

References 8 publications

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“…A stochastic model that describes this fluctuation should not dictate higher prices in winter, but the process should allocate a high probability that gas spot prices will rise when winter approaches. During the last two decades of the 20 th century, oil prices fluctuated around 18$/bll and although prices sometimes strongly deviated from this long-term average, the price of oil did revert back to a long-term market equilibrium price (Caldwell and Heather, 2001). Although today's price levels are clearly different, this reality does not necessarily imply that market mechanisms that dictated the existence of a long-term equilibrium oil price in the past are no longer operative.…”

Section: The Limitation Of Fixed Time Seriesmentioning

confidence: 93%

“…A detailed description of the process can be found in Luenberger (1998) and Begg and Smit (2007). Several authors have suggested that oil prices fluctuate around an equilibrium oil price (e.g., Caldwell and Heather, 2001). In this study, a stochastic model has been developed that addresses three sources of uncertainty: the oil spot price, the gas spot price, and a cost multiplier.…”

Section: Modeling Hydrocarbon Pricesmentioning

confidence: 98%

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Enhanced Economic Modeling by Correlated Stochastic Models of E&P Costs and Hydrocarbon Prices: The Limitations of Fixed Price Decks and the Versatility of Least-Squares Monte Carlo Simulation

Willigers¹

2009

EUROPEC/EAGE Conference and Exhibition

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As decision-making processes in the E&P industry increasingly rely on probabilistic economic models, determining the accuracy of its methodologies becomes more problematic. Enhancements can be achieved by (1) better understanding the interdependencies between different sources of uncertainty and (2) the abandonment of fixed time series of either hydrocarbon prices or capital expenditures.Historical market data of hydrocarbon prices, steel prices, and daily rig rental rates can be used to establish the correlation between different sources of market risk. Uncertainties can be defined as "fixed" or "dynamic." Fixed uncertainties relate to factors that do not change over time, such as many geological parameters during the early stages of exploration. Most uncertainties that relate to market risk are dynamic, that is, they keep developing over time. For example, not only is the realized price of oil uncertain until the moment the oil has been sold, but the expectation of future oil prices changes. The recognition of this Bayesian property of hydrocarbon prices significantly affects projects with multiple decision points. The forecasted hydrocarbon price at a future decision point is a function of the simulated realized price at that given decision point. Traditional decision tree models apply the same series of static price decks at each decision point and therefore do not accurately reflect the impact of the evolving market outlook during the development of a project.The stochastic model developed in this study accounts for (1) the correlation between different uncertainties and (2) Bayesian price-cost forecasts. The versatility of the Least-Squares Monte Carlo simulation technique is demonstrated by a real option valuation of an asset subjected to a complex tax regime and two future stage-gate decision points. IntroductionOver the past decade, the upstream oil and gas industry has slowly adapted the application of probabilistic or stochastic modeling techniques in place of traditional deterministic economic analysis (Bickel and Bratvold, 2007). Probabilistic modeling dictates that in contrast to single-point estimates for key model variables, a probability-weighted spectrum of potential outcomes is analyzed in an economic cash flow model. The fundamental notion of probabilistic modeling is that given a range of feasible outcomes, some are more likely to occur than others. Probabilistic modeling allows for a much improved understanding of the potential range of outcomes and how certain developments impact the economic performance of a project (Schuyler, 1998;Rose, 2001;Willigers, 2008a).A common approach in risk modeling is to identify the key uncertainties, decisions, and value drivers of an asset and to model several discrete probability-weighted outcomes in a probability or decision tree. This process can also approximate continuous probability distributions. The spectrum of feasible price scenarios is typically approximated using a combination of probability-weighted price decks. Though this approach provides a ...

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Section: The Limitation Of Fixed Time Seriesmentioning

confidence: 93%

Section: Modeling Hydrocarbon Pricesmentioning

confidence: 98%

Enhanced Economic Modeling by Correlated Stochastic Models of E&P Costs and Hydrocarbon Prices: The Limitations of Fixed Price Decks and the Versatility of Least-Squares Monte Carlo Simulation

Willigers¹

2009

EUROPEC/EAGE Conference and Exhibition

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Impact of Stimulation Net to Gross Ratio on Hydraulic Fracture Deliverability in Unconventional Resources

Ganpule

Waters

Al-Jalal

2015

SPE Western Regional Meeting

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We propose a novel concept relating to using net-to-gross (NTG) ratios in characterizing hydraulic fracture deliverability. Current NTG considerations applied in unconventional resources are primarily petrophysics-based. However, the variability of in-situ stress and material properties in the vertical direction greatly influence placement and vertical connectivity of a given hydraulic fracture. Hence, the areas of low connectivity within the created fracture system, such as pinch offs, can impact production performance and thus become a key asset development driver that ultimately influences project economics. Therefore, characterizing pinch offs in a created fracture network becomes a necessity. Such characterization can be accomplished by splitting NTG into two components—petrophysical (NTG-P) and stimulation (NTG-S). The focus of this work is the NTG-S. The proposed NTG-S is currently based on hydraulic fracture and production models coupled with calibration data from offset wells. For a given stress and material property profile, hydraulic fracture geometries are estimated using a fracture simulator with multiple calibration points. The post fracture closure width profile from the calibrated fracture model indicates possible pinch points along the created fracture height. The calibrated fracture geometry is then integrated into a production model, where the impact of the pinch points on well performance is simulated while honoring the actual production data. High-resolution stress logs and fullbore cores can help to address uncertainty in location and severity of pinch points and aid in reducing the non-uniqueness that is inherent to production models. NTG-S influences the productive fracture height, which in turn impacts the drainage volume and drainage area around a well. Subsequently, the drainage area affects well spacing and completion design considerations. For a given productive fracture surface area, overestimating NTG-S (assuming a large productive fracture height) can result in an assumed short drainage length, leading operators to laterally place offset wells closer than needed. Conversely, underestimating NTG-S can cause operators to space offset wells too far apart, resulting in lower recoveries. Consequently, in very thick unconventional reservoirs, stacked horizontal wells may be more appropriate. Accounting for NTG-S allows optimizing lateral landing points to ensure optimum drainage configuration is achieved.

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Maximizing Value of Information of a Horizontal Polymer Pilot Under Uncertainty

Steineder

Clemens

Osivandi

et al. 2018

SPE Europec Featured at 80th EAGE Conference and Exhibition

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Polymer injection might lead to incremental oil recovery and increase the value of an asset. Several steps have to be taken to mature a polymer injection project. The field needs to be screened for applicability of polymer injection, laboratory experiments have to be performed, and a pilot project might be required prior to field implementation. The decision to perform a pilot project can be based on a Value of Information (VoI) calculation. The VoI can be derived by performing a workflow capturing the impact of the range of geological scenarios as well as dynamic and polymer parameters on incremental Net Present Value (NPV). The result of the workflow is a Cumulative Distribution Function (CDF) of NPV linked to prior distributions of model parameters and potential observables from the polymer injection pilot. The impact of various parameters on the CDF of the field-wide NPV can be analyzed and in turn used to decide on what measurements from the pilot have a strong sensitivity on the NPV CDF and are thus informative. In the case shown here, the water cut reduction in the pilot area has a strong impact on the NPV CDF of the polymer injection field implementation. To extract maximum information, the response of the pilot for water cut reduction needs to be optimized under uncertainty. To calculate the VoI, the Expected Monetary Value (EMV) difference of a decision tree with and without the pilot can be used if the Decision Maker (DM) is risk neutral. However, if the DM requires hurdle values through a Probability of Economic Success (PES), Value Functions (VF) and Decision Weights according to the Prospect Theory should be used. Applying risk hurdles requires a consistent use of VFs and Decision Weights for calculating VoI and the Probability of Maturation (POM) of projects.

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Characterizing Uncertainty In Oil and Gas Evaluations

Abstract: TX 75083-3836, U.S.A., fax 01-972-952-9435.

Cited by 7 publications

References 8 publications

Enhanced Economic Modeling by Correlated Stochastic Models of E&P Costs and Hydrocarbon Prices: The Limitations of Fixed Price Decks and the Versatility of Least-Squares Monte Carlo Simulation

Enhanced Economic Modeling by Correlated Stochastic Models of E&P Costs and Hydrocarbon Prices: The Limitations of Fixed Price Decks and the Versatility of Least-Squares Monte Carlo Simulation

Impact of Stimulation Net to Gross Ratio on Hydraulic Fracture Deliverability in Unconventional Resources

Maximizing Value of Information of a Horizontal Polymer Pilot Under Uncertainty

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