The Role of Cut-offs in Integrated Reservoir Studies

Worthington, Paul F.; Luca, Cosentino

doi:10.2523/84387-ms

Cited by 19 publications

(24 citation statements)

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“…As mentioned earlier, conventionally net pays are determined by applying cut-off values on some petrophysical or well log data (Deakin and Manan, 1998;Svec and Grigg, 2000;Worthington, 2010;Worthington and Cosentino, 2005). In this work, to determine net pay zones by conventional method, the following process is utilized:…”

Section: Conventional Method: Based On Cut-offmentioning

confidence: 99%

“…Those intervals of net sand that contain porosity of higher than cut-off of porosity (between six to eight percent for sandstones and between four to five percent for carbonates) are classified as net reservoir that are capable of containing economical amounts of hydrocarbon in the rock pores. Finally, net pay is some part of net reservoir in which water saturation is less than cut-off of water saturation (the range of cut-off of water saturation is between five to six percent) (Worthington and Cosentino, 2005).…”

Section: Definition Of Net Pay and Cut-offmentioning

confidence: 99%

“…Worthington and Cosentino provided a comprehensive study on the role of cut-offs in determining net pays. They collected and summarized different combinations of cut-offs of shale volume, porosity, permeability, water saturation, resistivity and moveable hydrocarbon index (MHI), which have been used in 31 previous investigations from 1980 to 2002 (Worthington and Cosentino, 2005). A statistics-based procedure was introduced to determine cut-offs in a way to minimize error of calculating net to gross ratio (Jensen and Menke, 2006).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Application of Bayesian in determining productive zones by well log data in oil wells

Masoudi

Tokhmechi

Jafari

et al. 2012

Journal of Petroleum Science and Engineering

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Abstract:Exploration specialists conventionally utilize a cut-off-based method to find productive zones inside the oil wells. Using conventional method, pay zones are separated crisply from non-pay zones by applying cut-off values on some petrophysical features.In this paper, a Bayesian technique is developed to find productive zones (net pays), and Bayesian Network is used to select the most appropriate input features for this newly developed method. So, two Bayesian methods were developed: the first one with conventional pay determination inputs (shale percent, porosity and water saturation), the other with two inputs, selected by Bayesian Network (porosity and water saturation). Two developed Bayesian methods are applied on well log dataset of two wells: one well is dedicated for training and testing Bayesian methods, the other for checking generalization ability of the proposed methods. Outputs of two presented methods were compared with the results of conventional cut-offbased method and production test results (i.e. a direct procedure to check validation of proposed methods).Results show that the most prominent advantage of developed Bayesian method is determination of net pays fuzzily with no need to identify cut-offs, in addition to higher precision of classification: nearly 30% improvement in precision of determining net pays of first well (training well), and about 50% improvement in precision of determining productive zones through the generalizing well.

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Section: Conventional Method: Based On Cut-offmentioning

confidence: 99%

Section: Definition Of Net Pay and Cut-offmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Application of Bayesian in determining productive zones by well log data in oil wells

Masoudi

Tokhmechi

Jafari

et al. 2012

Journal of Petroleum Science and Engineering

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“…Petrophysical properties such as porosity and fluid saturation are the most important parameters controlling the amount of hydrocarbon in the reservoir, while permeability controls the reservoir fluid flow capacity (Worthington and Cosentino 2005). Initial values for petrophysical application are derived from core samples and well logs, while there distribution on the model is controlled by statistical or deterministic methods (Merletti and Torres-Verdin 2010;Worthington 2011).…”

Section: Literature Review Static and Dynamic Reservoir Modelingmentioning

confidence: 99%

Optimizing oil and gas field management through a fractal reservoir study model

Habib

Yao

Xie

et al. 2016

J Petrol Explor Prod Technol

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Integration among geophysics, geology, reservoir engineering, geochemists, geomechanics and management is truly essential, but needs some specific approaches and methodologies for developing and calibrating a study model capable of dealing with all and each of these aspects. The ability for a multitask project team to easily search, modify, visualize and/or analyze a multidisciplinary study results in a quick, responsive and easily comprehendible manner is still a problem of the petroleum industry. In this work, various modeling workflows were examined so as to highlight unavoidable interdependencies between these multidisciplinary specialists in the process of oil and/or gas reservoir studies. The traditional multidisciplinary working methods which were hitherto available are examined and some lapses identified. An optimized integrated study approach was further proposed. The optimized integrated approach is expected to have tremendous advantages in terms of improving the quality as well as flexibility of oil and gas reservoir studies, a working time reduction, and is expected to serve as a single final approach that can be adapted or used to tackle reservoir study problems.

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“…Alternatively, well logs, wireline tests, and well tests develop megascopic reservoir properties in form of moving averages with windows vary based on the individual log resolution. Worthington and Cosentino in [4] presented the effect of cutoffs value on integrated reservoir studies and highlighted the importance of petrophysical cutoffs on reservoir characterization for both static and dynamic models that inconsequence lead to realizations of the asset value.…”

mentioning

confidence: 99%

Well Log Petrophysics of the Cretaceous Pay Zones in Zubair Field, Basrah, South Iraq

Abdulaziz¹,

Dahab²,

Najmuddin³

2017

OJG

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Discovered in 1949 with a rate of (195,000) bbl/day from pay zones in Mishrif and Zubair Formation, the expected production of Zubair field is anticipated to be 1125 million bbl/day. Despite this production history, there is a major deficiency in detailed petrophysical analysis of the producing zones. In the present study well log data of 7 wells, selected from numerous wells, are investigated in details to examine the reservoir properties and characterize the reservoir architecture. The petrophysical analysis of Mishrif Formation indicated two or three pay zones. Lithologically, all zones of Mishrif Formation are dominantly clean limestone to dolomitic limestone with zone 2 and 3 reporting higher dolomitic content (20% to 40%) compared to zone 1 (6% to 13%). Mishrif pay zones indicated a relatively good porosity (18% -24%) with zone 2 predominant in secondary porosity associating dolomitization processes. In Zubair Formation one pay zone is identified but locally could separate into two zones. The clay content is generally low with average content between 2% and 3% while the average porosity showed slightly better values in zone 1 (~0.20) compared to average porosity of zone 2 (0.17) that is rich in silt content associating deposition at a relatively deeper parts of the shelf. The average water saturation shows distinct lower values that vary between 15% and 18.7%. The petrophysical results are statistically analyzed and property histograms and crossplots are constructed to investigate mutual relationships. Such analysis is essential for understanding the reservoir architecture and calculations of reservoir capacity for future development.

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The Role of Cut-offs in Integrated Reservoir Studies

Cited by 19 publications

References 0 publications

Application of Bayesian in determining productive zones by well log data in oil wells

Application of Bayesian in determining productive zones by well log data in oil wells

Optimizing oil and gas field management through a fractal reservoir study model

Well Log Petrophysics of the Cretaceous Pay Zones in Zubair Field, Basrah, South Iraq

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