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<br />SUMMARY
<br />
<br />This work has described several techniques for
<br />estimating aquifer specific yield and specific retention
<br />based on least-squares linear regression analysis using
<br />aquifer grain-size data, effective-porosity logs, and
<br />apparent grain-density logs. Specific retention can be
<br />estimated by use of any of five regression equations of
<br />specific retention on grain-size characteristics. Spe-
<br />cific yield then can be calculated from specific reten-
<br />tion by use of porosity values from density-porosity
<br />logs or from laboratory analyses. This technique is an
<br />alternative to determining specific yield and specific
<br />retention through laboratory analyses of undisturbed
<br />core samples. The regression technique is faster and
<br />less costly than the laboratory technique but can pro-
<br />duce specific-yield and specific-retention estimates of
<br />lesser accuracy than the laboratory technique, particu-
<br />larly if individual determinations are compared.
<br />Specific retention based on laboratory analyses
<br />of core was compared to corresponding specific reten-
<br />tion estimates derived from grain-size regression equa-
<br />tions. These direct comparisons were made for the
<br />regression data set, a separate verification data set, and
<br />a small data set representing an unconsolidated alluvial
<br />aquifer. In each case, the mean specific retention from
<br />the grain-size regression was comparable to that deter-
<br />mined by laboratory analyses.
<br />Effective-porosity logs and apparent grain-den-
<br />sity logs are produced as part of computer-assisted
<br />well-log evaluation programs available through com-
<br />mercial geophysical-logging companies. Regression
<br />analysis of specific yield on effective porosity provided
<br />a means for estimating specific yield from effective
<br />porosity, and a specific-yield log was produced.
<br />Regression analysis of specific yield divided by poros-
<br />ity data on apparent grain density provided another
<br />means for estimating specific yield. Both log interpre-
<br />tation techniques produced mean specific-yield esti-
<br />mates for the upper three bedrock aquifers in the
<br />Denver basin that are comparable to the mean values
<br />obtained from laboratory analyses of core.
<br />Errors in the production of density porosity logs
<br />and the magnitude of the standard error of estimate
<br />from the regression equations indicate the value of
<br />using a mean specific yield or specific retention for a
<br />geologic interval. Mean specific-yield values are good
<br />measures of the mean laboratory values, but individual
<br />regression and laboratory values can vary considerably.
<br />
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<br />
<br />18 Techniques for Estimating Specific Yield end Specific Retention from Greln-Slze Data and Geophysical Logs from
<br />Clastic Badrock Aquifers
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