Estimation of Finite Population Properties When Sampling is Without Replacement and Proportional to Magnitude

Andreatta, G.; Kaufman, Gordon M.

doi:10.2307/2288993

Cited by 16 publications

(15 citation statements)

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“…By drilling sweet spots with higher productivity than an average EUR in the early stage of shale gas development, better Monthly production, mmcf Monthly production, mmcf economic outcomes can be achieved. To illustrate this effect, we generated drilling sequences better than average statistically based on a sampling scheme adopted from ''discovery process'' models (Andreatta and Kaufman 1996;, commonly used in conventional petroleum resource assessment. Such a drilling sequence, which is affected by, but not exactly ranked by well EUR, is of probabilistic character in nature.…”

Section: When Someone Does Better Than the Averagementioning

confidence: 99%

“…Such a drilling sequence, which is affected by, but not exactly ranked by well EUR, is of probabilistic character in nature. The possible drilling sequence is formulated using the probabilistic model as a result of sampling from the parent population with a probability proportional to well EUR without replacement (Andreatta and Kaufman 1996). This probabilistic model and its application have been presented by Chen and Osadetz (2015) and will be discussed elsewhere in a separate paper.…”

Section: When Someone Does Better Than the Averagementioning

confidence: 99%

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Economic appraisal of shale gas resources, an example from the Horn River shale gas play, Canada

Chen

Osadetz

Chen³

2015

Pet. Sci.

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Development of unconventional shale gas resources involves intensive capital investment accompanying large commercial production uncertainties. Economic appraisal, bringing together multidisciplinary project data and information and providing likely economic outcomes for various development scenarios, forms the core of business decision-making. This paper uses a discounted cash flow (DCF) model to evaluate the economic outcome of shale gas development in the Horn River Basin, northeastern British Columbia, Canada. Through numerical examples, this study demonstrates that the use of a single average decline curve for the whole shale gas play is the equivalent of the results from a random drilling process. Business decision based on a DCF model using a single decline curve could be vulnerable to drastic changes of shale gas productivity across the play region. A random drilling model takes those drastic changes in well estimated ultimate recovery (EUR) and decline rates into account in the economic appraisal, providing more information useful for business decisions. Assuming a natural gas well-head price of $4/MCF and using a 10 % discount rate, the results from this study suggest that a random drilling strategy (e.g., one that does not regard well EURs), could lead to a negative net present value (NPV); whereas a drilling sequence that gives priority to developing those wells with larger EURs earlier in the drilling history could result in a positive NPV with various payback time and internal rate of return (IRR). Under a random drilling assumption, the breakeven price is $4.2/MCF with more than 10 years of payout time. In contrast, if the drilling order is strictly proportional to well EURs, the result is a much better economic outcome with a breakeven price below the assumed well-head price accompanied by a higher IRR.

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Section: When Someone Does Better Than the Averagementioning

confidence: 99%

Section: When Someone Does Better Than the Averagementioning

confidence: 99%

Economic appraisal of shale gas resources, an example from the Horn River shale gas play, Canada

Chen

Osadetz

Chen³

2015

Pet. Sci.

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“…The right-hand side of (4.1) is a version of Murthy's estimator which has been shown by Andreatta and Kaufman (1986) to have expectation 1/7rk(n). 0 Corollary 4.1: Let h be a single valued function with domain AN and range (-oc, co) or some subset of (-oo, oo The estimator H defined in (4.2) is a function of both s, and z(,+l) and is an unordered function of s,.…”

Section: Unbiased Estimationmentioning

confidence: 99%

“…In this application magnitudes of fields in order of discovery are observed and used to make predictions of the empirical frequencies of magnitudes of undiscovered fields. Logically tight theories of maximum likelihood, moment type and unbiased estimation for this class of problems have been developed by Bickel, Nair andWang, (1989), Gordon, (1989) and Andreatta and Kaufman, (1986). The problem of estimation of software reliability based on observation of times between failures of a software system may be viewed as the dual to the problem of inference when only magnitudes of population elements are observed.…”

Section: Introductionmentioning

confidence: 99%

Successive sampling and software reliability

Kaufman

1996

Journal of Statistical Planning and Inference

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“…The problem of finite population proportional to size sampling has previously been studied in the exploration context by a two-stage model due to G. M. Kaufman, see Kaufman, Balcer and Kruyt (1975), and Lee and Wang (1985). Other contributions to this area are Barouch and Kaufman (1967), Schuenemeyer and Drew (1983), Andreatta and Kaufman (1986), Kaufman (1992) and Chen andSindingLarsen (1994). Charpentier et.al.…”

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confidence: 99%

Log-Normal Creaming and the Likelihood of Discovering Additional Giant Petroleum Fields

Lillestøl

Sinding-Larsen

2016

SSRN Journal

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This paper considers sampling proportional to expected size from a partly unknown distribution. The applied context is the exploration for undiscovered resources, like oil accumulations in different deposits, where the most promising deposits are likely to be drilled first, based on some geologic size indicators ("creaming"). A Log-normal size distribution turns out to have nice analytical features in this context, and fits available data reasonably well. The theoretical and practical consequences for the accumulation of knowledge on the underlying distribution based on this scheme, named Log-normal creaming, are explored in some detail. The theory is applied on the prediction of remaining oil accumulations to be found on the Norwegian Continental Shelf.

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Estimation of Finite Population Properties When Sampling is Without Replacement and Proportional to Magnitude

Cited by 16 publications

References 0 publications

Economic appraisal of shale gas resources, an example from the Horn River shale gas play, Canada

Economic appraisal of shale gas resources, an example from the Horn River shale gas play, Canada

Successive sampling and software reliability

Log-Normal Creaming and the Likelihood of Discovering Additional Giant Petroleum Fields

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