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The emerging Vaca Muerta Formation, located in the Neuquén Basin in Southern Argentina, is the most successful Unconventional Play outside United States. In the last few years, several blocks have initialized multi-rig development programs and operators have identified interference between existing producers and newly fractured wells during the completion. The effect known as parent-child occurs when the reservoir depletion around the parent well modifies the pore pressure and induces variations in the original stress field. As a result of this effect, the parent well could be seriously damaged, the hydraulic fracture of the child well would be less efficient and there will be an unsymmetrical recovery around the child well. The parent-child effect is usually negative and impose an additional challenge on the drilling and completion sequence of the block. This contribution is an attempt to quantify the production impact of this effect using a combination of a multi-disciplinary workflow.
Unconventional reservoirs were originally developed by small oil and gas companies with stand-alone wells spread across the different basins. Later in time when major operators started to develop these projects that requires intensive capital expenditure, the factory mode was deployed to increase operational efficiency. This development strategy requires the adjustment of well spacing and completion designs to minimize well production interference while maximizing the recovery factors and economics. Despite many optimization studies have been looking for the perfect design, the ultimate recovery of wells drilled in factory mode are negatively impacted compared to a stand-alone well. Additionally, as the development of the blocks moved forward, some new wells (child) were placed next to wells on production (parent) and operators have seen an additional negative impact commonly called parent-child. Statistical data from different US Shale Plays confirmed the negative production impact of this effect (
Abstract Conventional oil price forecasting methods in the petroleum industry typically consider uncertainty by incorporating optimistic, pessimistic, and most-likely cases. Commonly, these price projections are "hockey stick" forecasts, i.e., forecasts that are initially flat or decline for some period of time and then increase monotonically. Review of historical forecasts by industry and governmental organizations show that conventional forecasting methods often fail to capture the true uncertainty associated with oil and gas prices. Performing discounted cash flow calculations using conventional oil and gas price forecasts will therefore underestimate the uncertainty associated with project economic performance indicators. Akilu et al. developed the Inverted Hockey Stick (IHS) Method to address these shortcomings. This new method for quantifying the uncertainty of price forecasts honors the historical extremes of oil and gas prices (on a constant dollar basis) along with the maximum positive and negative historical rates of change. To investigate the uncertainty associated with economic indicators (e.g., net present value, investment efficiency, and internal rate of return), we applied the IHS method to 23 completed or proposed projects from 12 operators. We found the P50 IHS value for these economic indicators is comparable to the most-likely value from conventional price forecasts. Across all 23 cases, however, the IHS method predicted a wider range of economic indicator values than conventional forecasts. The IHS method may be preferable over conventional methods due to its ability to quantify more realistic upside and/or downside risk associated with projects in the upstream petroleum industry. Introduction Investments throughout the oil and gas industry are subject to considerable uncertainty. Capen reports that uncertainty is difficult to quantify and that there is an almost universal tendency to underestimate it. Garb identified three classes of uncertainty for hydrocarbon-producing properties: technical, political, and economic. Many experts believe that economic uncertainty affects oil and gas investments at least as much as uncertainties in reservoir and technical data. Unlike technical uncertainty, however, economic uncertainty does not decrease over the life of a petroleum investment. While we may not be able to reduce economic uncertainty, we can make better investment decisions if we are able to quantify it. Conventional oil price forecasting methods traditionally attempt to address uncertainty by including optimistic, pessimistic, and most-likely cases. Commonly, these price projections are "hockey stick" forecasts. Hockey stick price forecasts are initially flat or decline for some period of time and then increase monotonically. Fig. 1 shows a natural gas price forecast published by the California Energy Commission (CEC) in 1998 that illustrates clearly the characteristic "hockey stick" shape of conventional price forecasts. Fig. 2 shows a later CEC natural gas price forecast, published in 2003, upon which subsequent actual gas price data are plotted. The figure shows that a significant portion of the actual gas price data fell well outside the price range represented by the pessimistic and optimistic cases during the first two years of the forecast. Another example further indicates the industry's tendency to underestimate the uncertainty in price forecasts. In the widely used textbook, Project Economics & Decision Analysis, Mian predicts "oil prices [will] remain in the range of $18 to $30 per barrel for another decade." Only two years after the publication of this text, during 2004, crude oil spot prices exceeded $56/bbl and closed the year at over $43/bbl. Caldwell and Heather noted, tongue in cheek, that nearly all conventional price forecasts are "wrong 100% of the time" and "nobody believe[s] the forecast anyway." Despite these observations and perceptions, conventional price forecasts are still widely used throughout the industry. According to Brashear et al., return on net assets averaged less than 7% for both majors and independents during the 1980's and 1990's. The apparent failure to recognize the true uncertainty in economic forecasting may have been a cause for these relatively low returns on investments in the petroleum industry.
Abstract Unconventional plays have moved to the forefront of the energy industry in the U.S. over the last five years due to advancements in technology and the overall abundance of producible hydrocarbons discovered near existing infrastructure. In the present economic climate, there is an increased interest in liquid rich plays, and because of the relatively limited historical production data available for these resources, there is a lot of industry discussion regarding future decline performance and estimated ultimate recovery (EUR) per well. The objective of this paper is to discuss the uncertainty associated with estimating reserves in U.S. unconventional plays using common decline curve analysis (DCA) methods in comparison to analytical modeling. Broadly speaking, there are five common methods for estimating: use of analogs, volumetric analysis combined with an estimate of recovery efficiency, decline curve analysis (DCA), analytical models and numerical simulation. Among theaforementioneds, DCA is the simplest and often fastest way to estimate volumes. However, the theoretical basis for most DCA approaches does not apply to unconventional reservoirs, which introduces some uncertainty into estimation of volumes. Nevertheless, it is commonly applied because of its perceived simplicity. Different unconventional DCA methods were compared with results of an analytical model generated using commercial software: the power law model (PLE), the logistic growth model (LGM), and Duong's method. The analysis was performed on various unconventional plays based on reservoir type and well geometry. All historical production data is gathered from public documents. The application of the DCA methods was also extended to various fluid types to determine their suitability for application in oil as well as gas reservoirs. The results of the study show that comparing multiple DCA methods with an analytical model aids in the understanding of the range of uncertainty associated with the EUR of unconventional wells. The study also helps establish the most appropriate DCA methods for various reservoir types, well geometry, and fluid types. The results also suggest approaches for avoiding violating the SEC's guidelines for categorizing proven reserves.
Abstract We collect a lot of data in order to decipher and understand our reservoirs, whether from logs and tests in exploration and appraisal wells to data regarding multiple parameters from production wells. There is often a trade-off between data gathering and time/cost to gather the data, but there is usually no compromising the analysis of such hard-earned data. What we often find however is that people fail to make the most of is the large amount of data in the public domain. This is often available free and, whilst often in raw form, rather than analysed, can be analysed and used to extract meaningful data. In this report we interrogate several public data sources and give several examples of analysis undertaken to reveal the regional scale trends for use in revealing unconventional exploration potential to production performance characteristics: CSG and water production data from Queensland; Unconventional resource estimate from SA, Queensland and the Northern Territory; Gas production and demand forecasts for the Australian East coast and how these can be linked with the respource estimates for the region; Gas and oil production data from South Australia; and Reserve, resource and production estimates from Wertern Australia. The methods used generally require only familiar tools such as Excel and ArcMap GIS spatial analysis. The results can be tailored according to the analysis required but may include any number of parameters, e.g. peak gas or water rate, ultimate gas recovery, gas in place per unit area, and regional trends in such parameters. We trust that this review will re-awaken analysts to the various public domain data that are available, which, although not always perfect, may provide valuable insights.
Several years into the "shale revolution," progress remains confined largely to North America. It is a viable question whether the shale oil and gas business will take off outside North America at all, or just at a slower pace. The reasons for slow growth vary from country to country but center around lack of infrastructure, ownership rights, government and public support, an active service sector that can support the activity, and whether such production makes sense economically. The growth in shale oil over the past few years has been impressive. Unconventional oil production in the Permian Basin, Eagle Ford, and other areas has lifted output in the state of Texas to 2.7 million BOPD.