A Petroleum Engineering Educational Model Based on the Maureen Field UKCS

Gringarten, Alain C.; Bond, Deryck; Jackson, Matthew D.; Xu-Dong, Jing; Mike, Ala; Johnson, Howard M.

doi:10.2523/64311-ms

Cited by 4 publications

(2 citation statements)

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“…The Maureen reservoir consists of Paleocene sandstones, which are interpreted to have been deposited as a broad submarine clastic fan across an extensive basin plain. 40,49 The oil is trapped in a four-way dip closure over a salt dome. The Maureen lithofacies is dominated by very clean, sand-rich, stacked massive sand sequences that characteristically show significant lateral facies variations and that are separated by shales of varying lateral extent.…”

Section: Impact Of Wettability Variation On Waterfloodingmentioning

confidence: 99%

“…The reservoir model used in this study was constructed using stochastic techniques conditioned to nine of the operator's exploration and development wells. 49 The model was designed to capture the architecture of the shales that separate the sandstones and the lateral and vertical variations in sandstone porosity and permeability. It was constructed on a grid containing 52×52×73 cells, which was sufficiently refined to capture the significant permeability heterogeneities, yet was not too large to be used directly for flow simulation (Fig.…”

Section: Impact Of Wettability Variation On Waterfloodingmentioning

confidence: 99%

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Prediction of Wettability Variation Within an Oil/Water Transition Zone and Its Impact on Production

2005

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We use a pore-scale network model in conjunction with conventional reservoir-scale simulations to investigate wettability variation within an oil/water transition zone. If the initial water saturation within the transition zone is controlled by primary drainage, we predict that initial production behavior is the same regardless of wettability. However, if the initial water saturation has been modified by movement of the free water level (FWL) following reservoir filling, then both the initial water saturation and production behavior are different depending upon wettability. In this case, the wettability of the reservoir may be estimated using in-situ measurements. Moreover, wettability variation may yield anomalous dry oil production from the transition zone. Over longer production timescales, wettability variation can result in high displacement efficiency during waterflooding. Assuming that the reservoir is uniformly water-wet or oil-wet, or using empirical hysteresis models, leads to a significant underestimate of recovery.

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Section: Impact Of Wettability Variation On Waterfloodingmentioning

confidence: 99%

Section: Impact Of Wettability Variation On Waterfloodingmentioning

confidence: 99%

Prediction of Wettability Variation Within an Oil/Water Transition Zone and Its Impact on Production

2005

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Using the Low Frequency Observation Data in Automatic History Matching

Faskhoodi¹,

Kelkar

2007

SPE Middle East Oil and Gas Show and Conference

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TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractIntegration of production data in reservoir description requires solving an inverse problem. Typically, a manual procedure is used to adjust the input parameters such that the productiodata can be history matched. Recently, many new techniques have emerged which try to accomplish this objective by using automated techniques. The two most common techniques involve gradient method and adjoint method. Both methods suffer from computationally demanding algorithms, except that gradient method is efficient if number of parameters is small and adjoint method is efficient if the number of observations is small.In a typical history matching of mature reservoir, we are faced with large number of input parameters and large number of observations.This would make both the procedures inefficient.This study proposes a technique to reduce the number of observed data so that history matching can be accomplished more efficiently. Using the low frequency information, we demonstrate that the history matching is more efficient. We further show that the low frequency data provides more robust estimate of input parameters compared to the use of all the available data. The proposed method is validated using a synthetic example as well as actual field example.

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Evaluation of Confidence Intervals in Well Test Interpretation Results

Azi

Gbo

Whittle³

et al. 2008

Europec/Eage Conference and Exhibition

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Uncertainty in well test analysis results from errors in pressure and rate measurements, from uncertainties in basic well and reservoir parameters; from the quality of the match with the interpretation model; and from the non-uniqueness of the interpretation model. Yet, well test analysis results are usually reported as unique values, often with unrealistic precision. Most well test interpretation software programmes use non-linear regression to determine the reservoir parameters that provide the best match between actual rate and pressure data and a given interpretation model. The non-linear regression evaluates the match quality as a standard correlation between each parameter. This, however, only estimates the match errors, and does not incorporate the other errors that must be accounted for to understand the overall uncertainty on the analysis. The paper presents a practical methodology for the determination of error bounds in well test analysis and illustrates its application with well tests from an oil reservoir and a gas condensate reservoir in the North Sea in order to evaluate typical error bounds for the most common parameters such as permeability-thickness, permeability, skin effect, fracture, horizontal well lengths and distances to boundaries. Differences in error bounds between hand and computer analysis are also discussed. Introduction Uncertainty in well test analysis results from errors in pressure and rate measurements, from uncertainties in basic well and reservoir parameters; from the quality of the match with the interpretation model; and from the non-uniqueness of the interpretation model (Horne 1994). Yet, well test analysis results are usually reported as unique values, often with unrealistic precision. This has been exacerbated by the use of hand calculators and, later on, computers and well test interpretation software for performing well test analysis calculations, because engineers, students and professionals alike, seem to believe that because the tools they use display eight decimal places, all eight places are accurate. Consequently, distances to boundaries are often reported with a resolution of a tenth of a foot, skin with two decimal digits, and permeabilities greater than 100 mD within 0.1 mD, i.e. with resolutions better than 0.1%, which is utterly ridiculous.

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A Petroleum Engineering Educational Model Based on the Maureen Field UKCS

Cited by 4 publications

References 0 publications

Prediction of Wettability Variation Within an Oil/Water Transition Zone and Its Impact on Production

Prediction of Wettability Variation Within an Oil/Water Transition Zone and Its Impact on Production

Using the Low Frequency Observation Data in Automatic History Matching

Evaluation of Confidence Intervals in Well Test Interpretation Results

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