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  <controlfield tag="008">260224s2010    xxu                      </controlfield>
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    <subfield code="a">Bouffin, N.</subfield>
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    <subfield code="a">Jensen, J.L.</subfield>
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    <subfield code="a">Efficient detection of productive intervals in oil and gas reservoirs</subfield>
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    <subfield code="c">mar. 2010</subfield>
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    <subfield code="a">14/06/2010 ; 10/06/2010</subfield>
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    <subfield code="a">6 p. ; 58-63</subfield>
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    <subfield code="a">Transcripci&#xF3;n del resumen del autor. The utility and evaluation of cutoff values for net pay or net-to-gross determination have been hotly debated topics since the 1950s. There are numerous subtleties to cutoffs, but exactly how the values are calculated has largely been overlooked. Most cutoff users have been content to use a regression line to calculate the cutoff value. We show that cutoffs obtained using a regression line are likely to be inferior to estimates produced by other methods. When four methods were applied to two field datasets and compared, regression-based porosity cutoffs were between 1 and 2 pu different than the values that give the smallest number of errors. Monte Carlo simulations broadly support the results obtained from the datasets. One method, the "trial-and-error" method, performed well through most of the tests, reducing errors by 40% from those obtained using the regression line-based cutoff. All cutoff estimation methods have errors, caused by the imperfect relationships we have between variables, such as porosity and permeability. This study shows we have a choice of methods. Because the better method can be easily applied in spreadsheet software, this should be a valuable addition to the petrophysicist's toolbox.</subfield>
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  <datafield tag="773" ind1="0" ind2=" ">
    <subfield code="t">Journal of Canadian Petroleum Technology</subfield>
    <subfield code="g">49</subfield>
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    <subfield code="r">2026-03-05 15:13:16</subfield>
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