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<br />yield on apparent grain density. Apparent grain- <br />density data were obtained from the apparent grain- <br />density log for well USGS. Testing of various <br />regression equation models indicated that the regres- <br />sion equation that had the largest coefficient of correla- <br />tion and the smallest standard error of estimate had <br />specific yield divided by porosity as the dependent <br />variable. This regression equation was used in this <br />report; specific yield and specific retention were calcu- <br />lated by using porosity values from the density porosity <br />log. The regression equation (fig. 7) has a coefficient <br />of correlation of 0.90 and a standard error of estimate <br />of 0.13 (in units of specific yield divided by porosity). <br />At a porosity of 0.30, this standard error is equivalent <br />to 0.04 specific-yield units. The correlation is adequate <br />to enable estimation of specific yield divided by poros- <br />ity from the apparent grain-density log. Mean values of <br />specific yield calculated from core and from the appar- <br /> <br />1,0 <br /> <br />, <br />, <br /> <br /> <br />ent grain-density log and density porosity log are listed <br />in table 3. Values calculated by this technique agree <br />closely with those calculated from core analyses and <br />from the effective porosity technique. <br /> <br />The regression equation of specific yield on <br />effective porosity was used with geophysical logs for <br />the lower 200 ft of well USGS to calculate a specific- <br />yield log for this interval (fig. 8). Except for washout <br />intervals, a continuous specific-yield log can be calcu- <br />lated, and log values can be averaged to determine the <br />mean specific yield of intervals or for entire aquifers. <br />An estimated mean specific yield of 0.14 was calcu- <br />lated for this 200-ft interval by using the regression <br />equation of specific yield on effective porosity. The <br />specific-yield log produced by using the regression <br />equation of specific yield divided by porosity on appar- <br />ent grain density was similar to that in figure 8. <br /> <br />o <br /> <br /> " . LINE OF REGRESSION - <br /> " . <br /> " .... (SY/l/l =' 6.819 - 2.253 Pfha) <br /> .. ~. <br /> 0,8 : :. ....... :t ONE STANDARD ERROR 0,2 <br /> , . , . OF ESTIMATE <br /> , . . . . , <br /> , . . , <br />-------- .... , <br />~I~ , , <br /> , . , <br /> , . , . z <br />--------- 0,6 , . , 0,' 0 <br /> . . , , f= <br />0 , , . <br />...J , , Z ~ <br />w ~ , , W <br />>= , , f- (ii <br />(ii , , W 0 <br /> . a; <br />U 0 . . , , a; <br />u: a; 0,' ,. , 0,6 !,1 0 <br />U 0 . , . , LL. ll. <br />W ll. ,. , U <br />ll. , , W <br />en . , , ll. <br /> , , en <br /> , , <br /> , , <br /> 0,2 , 0,8 <br /> , <br /> , <br /> , <br /> , <br /> , <br /> , <br /> "- <br /> 0 1,0 <br /> 2.60 2.70 2.80 2,90 3.00 <br /> APPARENT GRAIN DENSITY (Pma), IN GRAMS PER CUBIC CENTIMETER <br />Figure 7. Unear regression relation of specific yield divided by porosity on apparent grain density. <br /> <br /> <br />18 Techniques for EsUrnatlng Specific Yield and Specific Ratentlon from Graln-S1za Data and Geophysical Logs from <br />eluUc Badrock Aquila.. <br />