A practical approach for optimization of infill well placement in tight gas reservoirs

Cheng, Yueming; McVay, Duane A.; Lee, W. John

doi:10.1016/j.jngse.2009.10.004

Cited by 15 publications

(4 citation statements)

References 16 publications

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“…The upstream exploration and production industry employs a range of tools (see the Tools section), data banks, and heuristics (e.g., uniform well spacing in set patterns). However, several studies have challenged such heuristics. A multidisciplinary engineering team identifies several development scenarios and assesses them via extensive simulations to estimate field‐flow profiles.…”

Section: Oil‐field Designmentioning

confidence: 99%

Process systems engineering perspective on the planning and development of oil fields

Tavallali

Karimi

Baxendale³

2016

AIChE Journal

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Section: Oil‐field Designmentioning

confidence: 99%

Process systems engineering perspective on the planning and development of oil fields

Tavallali

Karimi

Baxendale³

2016

AIChE Journal

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“…Research is done to place the laterals in the most productive shale, more quartz content, less clay, this can guarantee created fracture to be optimum and more complex. Cheng et al (2009) presented a methodology of optimization of infill wells in tight gas reservoirs using sequential inversion algorithm for rapid history matching and successive selection strategy for infill candidate well locations. Wilson et al (2012) presented a general framework for applying optimization to the development of shale gas reservoirs.…”

Section: Well Placement In Unconventional Reservoirsmentioning

confidence: 99%

Fracturability Index is a Mineralogical Index: A New Approach for Fracturing Decision

et al. 2015

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Shale has ultra-low matrix permeability, and consequently requiring the creation of hydraulic fracturing to maximize the contact area with the reservoir. The key to successful fracturing treatment in shale formation is the identification of the sweet spots. Productive shale consists of quartz, feldspar or carbonate and clays, in addition to organic matter (Kerogen). Thus it is challenging process to map the best zones to fracture and locate horizontal wells. A new Fracturability Index based on mineralogy has been developed to locate the best areas along horizontal wells to fracture. A good Mineralogical Index would prolong production plateau for shale plays.Current technology follow two schools, first one through equally spaced fracturing, and the more fractures the better production, second; guide through brittleness index, which distinguish brittle versus ductile zones along the well path, supporting the second school, we have a better correlation of Fracturability index, the new correlation indicates the most brittle parts of the reservoir (MI>0.6) versus the most ductile parts (MI <0.6), it became easier to map the producing shale with sweet or unattractive spots leading to the effective fracture locations. It is a new sweet spot identifiers, which guide the fracture design and fracture allocation along horizontal wellbore path, it may optimize well placement and hydraulic fracturing positioning in unconventional resources.A new Minerological Index is developed ranging from 0 to 1 which helps optimize the fracturing and shale development, in addition to guaranteeing fracture treatments are in the right place. This will facilitate connectivity with natural fracture network, priority of guiding fracture design start with High FI which corresponds to higher mineralogy index. MI value of 0.6 is a good starting point to map sweet spots. This may enhance far field Fracturing Complexity and help getting a branched fracture. Based on a sub category of quartz, type of treatment may be recommended.

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“…These methods are important for unconventional resources because they can provide values for key variables such as fracture half-length, fracture conductivity, and formation permeability (Mattar et al 2006;Cheng et al 2009;Clarkson et al 2009;. Straight-line methods rely on logarithmic plots of production (or scaled production for variable flowing pressure) against time and focus on straight-line segments of such plots to generate estimates of key variables for a specific flow regime.…”

Section: Background and Related Literaturementioning

confidence: 99%

Analysis of Production History for Unconventional Gas Reservoirs With Statistical Methods

Bhattacharya

Nikolaou

2013

SPE Journal

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Unconventional gas resources have dramatically changed the future energy landscape. Developing these resources involves substantial risk. Such risk can be mitigated if information gathered at initial stages of the development of a field is used efficiently and effectively to guide future development. A variety of tools-such as decline-curve analysis (DCA), type-curve analysis, simulator history matching, and artificial intelligence (AI)-is used to that effect. These tools accomplish partially overlapping but different tasks. Additional tools that could not only facilitate the analysis of historical data but also guide future development would be of value. In this work, we propose an efficient methodology that can use historical production data from existing wells to answer questions such as the following: Which wells will behave similarly? Which wells will behave differently from each other or from standard expectations? Which factors will contribute to these differences? How can data from existing wells be used to anticipate the performance of new wells? The proposed methodology relies on standard principal-component analysis (PCA) and principal-component regression (PCR). The application of PCA to historical production data from twelve wells in the Holly Branch field quickly identified wells with distinct behavior. The subsequent investigation of pressure and the completion data for these wells revealed reasons for such distinct behavior. Finally, a simple linear model was built with PCR, with good ability to predict production from new wells, as assessed through cross-validation. The value of the efficiency offered by the proposed methodology would be much higher for larger data sets, for which manual analysis of production data is more cumbersome.

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A practical approach for optimization of infill well placement in tight gas reservoirs

Cited by 15 publications

References 16 publications

Process systems engineering perspective on the planning and development of oil fields

Process systems engineering perspective on the planning and development of oil fields

Fracturability Index is a Mineralogical Index: A New Approach for Fracturing Decision

Analysis of Production History for Unconventional Gas Reservoirs With Statistical Methods

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