A New Approach to Large-Scale Infill Evaluations Applied to the OZONA (Canyon) Gas Sands

Voneiff, G.W.; Cipolla, Craig L.

doi:10.2118/35203-ms

Cited by 41 publications

(13 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Our approach was to integrate the available data and use analytical tools and some small conceptual models. This is not unlike moving-mosaic techniques used for infill drilling (Voneiff and Cipolla 1996;Guan et al 2002;Hudson et al 2000;Hudson et al 2001;Wozinak et al 1997) or the quality-map approach (da Cruz et al 2004). A frequent approach to analytical simulation consists of modeling a well pattern (generally five-spot patterns), with the assumption that the obtained results represent the average performance of a particular sector of the reservoir.…”

Section: Field Cases Type I: Lack Of Data and Time Constraintsmentioning

confidence: 99%

Effective EOR Decision Strategies With Limited Data: Field Cases Demonstration

Manrique

Izadi

Kitchen

et al. 2009

SPE Reservoir Evaluation &Amp; Engineering

View full text Add to dashboard Cite

Enhanced-oil-recovery (EOR) evaluations focused on asset acquisition or rejuvenation involve a combination of complex decisions using different data sources. EOR projects traditionally have been associated with high capital and operational expenditures (CAPEX and OPEX, respectively) as well as high financial risk, which tend to limit the number of EOR projects launched. We propose a workflow for EOR evaluations that accounts for different volumes and quality of information. This flexible workflow has been applied successfully to oil-property evaluations and EORfeasibility studies in many oil reservoirs. The method associated with the workflow relies on traditional (e.g., look-up tables, x-y correlations) and more-advanced (data mining for analog-reservoir search and geology indicators) screening methods, emphasizing identification of analogs to support decision making. The screening phase is combined with analytical or simplified numerical simulations to estimate full-field performance with reservoir-data-driven segmentation procedures. This paper illustrates the EOR decision-making workflow by use of field case examples from Asia, Canada, Mexico, South America, and the United States. The assets evaluated include reservoir types ranging from oil sands to condensate reservoirs. Different stages of development and information availability are discussed. Results show the advantage of a flexible decision-making workflow that can be adapted to the volume and quality of information by formulating the correct decision problem and concentrating on projects and/or properties with the highest expected economic merit. An interesting aspect of this approach is the combination of geologic and engineering data, minimizing experts' bias and combining technical and financial figures of merit. The proposed method has proved useful to screen and evaluate projects/properties very rapidly, identifying when upside potential exists.

show abstract

Section: Field Cases Type I: Lack Of Data and Time Constraintsmentioning

confidence: 99%

Effective EOR Decision Strategies With Limited Data: Field Cases Demonstration

Manrique

Izadi

Kitchen

et al. 2009

SPE Reservoir Evaluation &Amp; Engineering

View full text Add to dashboard Cite

show abstract

“…Our approach is to integrate the available data and use analytical tools and some small conceptual models. This is not unlike moving mosaic techniques used for infill drilling (Voneiff and Cipolla, 1996;Guan et al, 2002;Hudson, Jochen and Jochen, 2000;Hudson, Jochen and Spivey, 2001;Wozinak, Wing and Schrider, 1997) or the quality map approach (Da Cruz, Horne, and Deutsch, 2004). A frequent approach to analytical simulation consists of modeling a well pattern (generally 5-spot patterns), with the assumption that the obtained results represent the average performance of a particular sector of the reservoir.…”

Section: Case Study Cmentioning

confidence: 99%

Effective EOR Decision Strategies with Limited Data: Field Cases Demonstration

et al. 2008

View full text Add to dashboard Cite

Enhanced-Oil Recovery (EOR) for asset acquisition or rejuvenation involves intertwined decisions. In this sense, EOR operations are tied to a perception of high investments that demand EOR workflows with screening procedures, simulation and detailed economic evaluations. Procedures have been developed over the years to execute EOR evaluation workflows.We propose strategies for EOR evaluation workflows that account for different levels of available information. These procedures have been successfully applied to oil property evaluations and EOR applicability in a variety of oil reservoirs. The methodology relies on conventional and unconventional screening methods, emphasizing identification of analogues to support decision making. The screening phase is combined with analytical or simplified numerical simulations to estimate full-field performance while maintaining rational reservoir segmentation procedures. This paper fully describes the EOR decision-making procedures using field case examples from Asia, Canada, Mexico, South America and the United States. The type of assets evaluated includes a spectrum of reservoir types, from oil sands to light oil reservoirs. Different stages of development and information availability are discussed. Results show the advantage of flexible decision-making frameworks that adapt to the volume and quality of information by formulating the correct decision problem and concentrate on projects and/or properties with apparent economic merit.Our EOR decision-making approaches integrate several evaluation tools, publicly or commercially available, whose combination depends on availability and quality of data. The decision is laid out using decision-analysis tools coupled with economic models and numerical simulation. This allows integrated teams to collaborate in the decision making process without over-analyzing the available data. One interesting aspect is the combination of geologic and engineering data, minimizing experts' bias and combining technical and financial figures of merit rationally. The proposed methodology has proved useful to screen and evaluate projects/properties very rapidly, identifying whether or not upside potential exists.

show abstract

“…However, some low-permeability reservoirs take from 9 to 14 years to reach boundary-dominated flow. 5 Thus, we may not be able to apply moving window technology in some gas fields with short production histories, e.g., less than 10 years.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Despite these assumptions and limitations, this moving domain technique has been applied to the Ozona (Canyon) gas sands, 5 Milk River formation in Canada, 8 Cotton Valley in east Texas, 4,9 Mesaverde formation in the San Juan Basin, 9 They estimated ultimate recoveries (EUR) on a barrels/acre basis by calculating every well's EUR and drill density. Then they analyzed the depletion and infill potential.…”

Section: Literature Reviewmentioning

confidence: 99%

“…[1][2][3][4][5][8][9][10] In particular, the moving domain technology, described by McCain et al 4 and enhanced by Voneiff and Cipolla 5 has been applied to several tight gas reservoirs to quantify infill potentials. 4,5,8,9 Although the moving domain technology has been applied to several tight gas reservoirs, we could not find any quantitative assessment of the validity and accuracy of the technique in the literature.…”

Section: Project Objectivesmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of a Statistical Infill Candidate Selection Technique

et al. 2002

View full text Add to dashboard Cite

Quantifying the drilling or recompletion potential in producing gas basins is often a challenging problem, because of large variability in rock quality, well spacing, and well completion practices and the large number of wells involved. Complete integrated reservoir studies to determine infill potential are often too time-consuming and costly for many producing gas basins.In this work we evaluate the accuracy of a statistical moving-window technique that has been used in tight-gas formations to assess infill and recompletion potential.The primary advantages of the technique are its speed and its reliance upon well location and production data only.We used the statistical method to analyze simulated low-permeability, 100-well production data sets, then compared the moving-window infill-well predictions to those from reservoir simulation. Results indicate that moving-window infill predictions for individual wells can be off by more than 50%; however, the technique accurately predicts the combined infill-production estimate from a group of infill candidates, often to within 10%.We found that the accuracy of predicted infill performance decreases as heterogeneity increases and increases as the number of wells in the project increases.The cases evaluated in this study included real-world well spacing and production rates and a significant amount of depletion at the infill locations. Because of its speed, accuracy and reliance upon readily available data, the moving window technique can be a useful screening tool for large infill development projects.

show abstract

A New Approach to Large-Scale Infill Evaluations Applied to the OZONA (Canyon) Gas Sands

Cited by 41 publications

References 0 publications

Effective EOR Decision Strategies With Limited Data: Field Cases Demonstration

Effective EOR Decision Strategies With Limited Data: Field Cases Demonstration

Effective EOR Decision Strategies with Limited Data: Field Cases Demonstration

Evaluation of a Statistical Infill Candidate Selection Technique

Contact Info

Product

Resources

About