curvatheis (2) - copia
DESCRIPTION
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Prueba de Bombeo con Método de Theis.PNE PNE PNE Pbombeo
t(dias) t seg PO-1 65.35 PO-2 67.36 PO-3 76.340 0 65.35 67.36 76.34
3.472222E-05 3 65.7 67.8 76.60.0034722222 300 67.8 68.3 77.20.0208333333 1800 69.7 71.2 77.30.0416666667 3600 73.4 73.6 77.6
0.125 10800 76.5 73.9 77.90.25 21600 77.2 74.2 81.1
0.375 32400 78.2 74.7 81.20.5 43200 78.2 75.13 81.4
0.625 54000 78.2 75.13 81.40.75 64800 78.2 75.13 81.4
ACUIFERO SEMICONFINADO
T=0.366Q/m m=dslog
T=K*b
0.00001 0.0001 0.001 0.01 0.1 155
60
65
70
75
80
f(x) = 1.46798923059014 ln(x) + 78.5492217233297R² = 0.885162948424874
Chart Title
0.00001 0.0001 0.001 0.01 0.1 164
66
68
70
72
74
76
f(x) = 0.850457171799701 ln(x) + 75.3649284511954R² = 0.883249865373569
Chart Title
b 225 m Preguntas PNE Q=
90 l/s65.35 7776 m3/dia Rmax
r1 1 m Tpromedior2 15 m Kr3 94 m
rbombeo 0.3048 m Es 100% eficiente ¿?
83.4
0.00001 0.0001 0.001 0.01 0.1 164
66
68
70
72
74
76
f(x) = 0.850457171799701 ln(x) + 75.3649284511954R² = 0.883249865373569
Chart Title
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.874
75
76
77
78
79
80
81
82
f(x) = 0.556897544906274 ln(x) + 80.918194475028R² = 0.66554670094337
Chart Title
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.874
75
76
77
78
79
80
81
82
f(x) = 0.556897544906274 ln(x) + 80.918194475028R² = 0.66554670094337
Chart Title
u w(u)Fortran 1/u w(u)Matlab w(u)Excel 5 w(u)J-C1E-10 22.449597456 10000000000 22.44863526514 22.449597500952 22.449597500852E-10 21.756450276 5000000000 21.75548808468 21.756450320492 21.756450320293E-10 21.350985168 3333333333 21.35002297667 21.350985212484 21.350985212184E-10 21.063303095 2500000000 21.06234090432 21.063303140132 21.063303139735E-10 20.840159544 2000000000 20.8391973531 20.840159588918 20.840159588426E-10 20.657837988 1666666667 20.65687579641 20.657838032224 20.657838031627E-10 20.503687308 1428571429 20.50272511668 20.503687352497 20.50368735188E-10 20.370155915 1250000000 20.36919372416 20.370155959972 20.370155959179E-10 20.25237288 1111111111 20.2514106886 20.252372924416 20.252372923521E-09 20.147012364 1000000000 20.14605017304 20.147012408858 20.147012407862E-09 19.453865185 500000000 19.45290299348 19.453865229298 19.45386522733E-09 19.048400078 333333333.33 19.04743788638 19.04840012219 19.048400119194E-09 18.760718006 250000000 18.75975581492 18.760718050738 18.760718046745E-09 18.537574456 200000000 18.53661226461 18.537574500424 18.537574495426E-09 18.3552529 166666666.67 18.35429070882 18.35525294463 18.355252938637E-09 18.201102221 142857142.86 18.20014002999 18.201102265803 18.20110225888E-09 18.06757083 125000000 18.06660863837 18.067570874178 18.067570866189E-09 17.949787795 111111111.11 17.94882560371 17.949787839522 17.949787830521E-08 17.84442728 100000000 17.84346508905 17.844427324864 17.844427314862E-08 17.15128011 50000000 17.15031791849 17.151280154304 17.15128013433E-08 16.745815012 33333333.333 16.74485282038 16.745815056196 16.74581502624E-08 16.458132949 25000000 16.45717075793 16.458132993744 16.458132953745E-08 16.234989408 20000000 16.23402721662 16.23498945243 16.234989402436E-08 16.052667861 16666666.667 16.05170566982 16.052667905636 16.052667845647E-08 15.898517191 14285714.286 15.897555 15.898517235809 15.898517165818E-08 15.764985809 12500000 15.76402361737 15.764985853184 15.764985773189E-08 15.647202783 11111111.111 15.64624059171 15.647202827528 15.64720273753
0.0000001 15.541842277 10000000 15.54088008606 15.54184232187 15.541842221870.0000002 14.848695197 5000000 14.8477330055 14.84869524131 14.848695041310.0000003 14.443230189 3333333.3333 14.44226799739 14.443230233202 14.44322993320.0000004 14.155548216 2500000 14.15458602494 14.15554826075 14.155547860750.0000005 13.932404765 2000000 13.93144257362 13.932404809436 13.932404309440.0000006 13.750083308 1666666.6667 13.74912111683 13.750083352642 13.750082752640.0000007 13.595932728 1428571.4286 13.594970537 13.595932772814 13.595932072810.0000008 13.462401436 1250000 13.46143924438 13.46240148019 13.462400680190.0000009 13.3446185 1111111.1111 13.34365630872 13.344618544533 13.34461764453
0.000001 13.239258084 1000000 13.23829589306 13.239258128876 13.239257128880.000002 12.546111904 500000 12.5451497125 12.546111948315 12.546109948320.000003 12.140647796 333333.33333 12.13968560439 12.140647840205 12.140644840210.000004 11.852966723 250000 11.85200453194 11.852966767752 11.852962767760.000005 11.629824172 200000 11.62886198062 11.629824216435 11.629819216440.000006 11.447503615 166666.66667 11.44654142383 11.447503659639 11.447497659650.000007 11.293353935 142857.14286 11.292391744 11.293353979808 11.293346979820.000008 11.159823543 125000 11.15886135137 11.15982358718 11.15981558720.000009 11.042041507 111111.11111 11.04107931571 11.042041551519 11.04203255154
0.00001 10.936681991 100000 10.93571980004 10.936682035857 10.936672035880.00002 10.243544811 50000 10.24258261941 10.243544855222 10.24352485532
0.00003 9.8380897023 33333.333333 9.837127511176 9.8380897469887 9.8380597472140.00004 9.5504176297 25000 9.549455438549 9.5504176743619 9.5503776747620.00005 9.3272840782 20000 9.32632188701 9.3272841228227 9.3272341234480.00006 9.1449725211 16666.666667 9.144010329941 9.1449725657537 9.1449125666540.00007 8.9908318409 14285.714286 8.989869649788 8.9908318856015 8.9907618868260.00008 8.8573104479 12500 8.856348256789 8.857310492602 8.8572304942020.00009 8.7395374119 11111.111111 8.738575220708 8.7395374565206 8.739447458546
0.0001 8.6341868957 10000 8.633224704575 8.6341869403878 8.6340869428880.0002 7.9411397077 5000 7.940177516515 7.9411397523282 7.9409397623280.0003 7.5357745871 3333.3333333 7.534812395908 7.5357746317211 7.535474654220.0004 7.2481924971 2500 7.247230305958 7.2481925417714 7.2477925817680.0005 7.0251489233 2000 7.024186732147 7.0251489679606 7.0246490304540.0006 6.842927339 1666.6666667 6.841965147859 6.8429273836717 6.842327473660.0007 6.6888766267 1428.5714286 6.687914435538 6.6888766713515 6.6881767938320.0008 6.5554451966 1250 6.554483005423 6.5554452412363 6.5546454012080.0009 6.4377621184 1111.1111111 6.436799927279 6.437762163092 6.436862365552
0.001 6.3325015553 1000 6.331539364136 6.3325015999492 6.3315018498940.002 5.6403536251 500 5.639391433965 5.640353669778 5.6383546693340.003 5.2358872681 333.33333333 5.234925076912 5.2358873127247 5.2328895612260.004 4.9492034477 250 4.948241256514 4.9492034923267 4.9452074887740.005 4.7270576497 200 4.726095458584 4.7270576943975 4.722063937460.006 4.545733348 166.66666667 4.544771156839 4.5457333926521 4.5397423806660.007 4.3925794252 142.85714286 4.391617234056 4.392579469869 4.3855917008380.008 4.2600442919 125 4.259082100803 4.2600443366157 4.2520603082140.009 4.1432570183 111.11111111 4.142294827176 4.1432570629892 4.134277272557
0.01 4.0388917677 100 4.037929576538 4.0388918123512 4.02891675690.02 3.3556699745 50 3.35470778331 3.3556700191228 3.335769576340.03 2.9600809152 33.333333333 2.959118724021 2.9600809598345 2.9303044682320.04 2.6822258802 25 2.681263689025 2.6822259248393 2.642622395780.05 2.4688606797 20 2.46789848851 2.4688607243267 2.4194788444660.06 2.2962691093 16.666666667 2.295306918144 2.2962691539676 2.2371572876720.07 2.1518003714 14.285714286 2.150838180257 2.1518004160969 2.0830066078440.08 2.0279031937 12.5 2.026941002586 2.0279032384589 1.949475215220.09 1.9197069612 11.111111111 1.918744770033 1.9197070059674 1.831692179563
0.1 1.8238861496 10 1.822923958419 1.8238861944612 1.7263316639060.2 1.2236127353 5 1.222650544184 1.2236127944568 1.0331844833460.3 0.9066388428 3.3333333333 0.905676651676 0.9066390502375 0.6277193752370.4 0.70334231 2.5 0.702380118866 0.7033432583413 0.3400373027860.5 0.5607357859 2 0.559773594776 0.5607392375826 0.1168937514710.6 0.4553416943 1.6666666667 0.454379503189 0.4553517946775 -0.0654278053220.7 0.3747310343 1.4285714286 0.373768843234 0.3747561454058 -0.219578485150.8 0.3115587695 1.25 0.310596578546 0.3116140333369 -0.3531098777740.9 0.2611461298 1.1111111111 0.260183939326 0.2612568615694 -0.470892913431
1 0.2203461234 1 0.219383934396 0.2205521264671 -0.5762534290882 0.0498586609 0.5 0.048900510708 0.0617105014627 -1.2694006096483 0.0136831853 0.3333333333 0.013048381094 0.1363842822434 -1.6748657177574 0.0037793524 0.25 0.00377935241 0.6330077653472 -1.9625477902085 0.0011482956 0.2 0.001148295591 2.2066697695886 -2.185691341523
6 0.0003600825 0.1666666667 0.000360082452 6.0919871016835 -2.3680128983177 0.0001154817 0.1428571429 0.000115481732 14.284641977412 -2.5221635781448 3.766562E-05 0.125 3.766562284E-05 29.735416140343 -2.6556949707689 1.244735E-05 0.1111111111 1.244735418E-05 56.547771993575 -2.773478006425
1E-100.000000010.0000010.00010.0111001
10
100
Chart Titlew(u)Matlab w(u)Excel 5 w(u)J-C
1E-100.000000010.0000010.00010.0111001
10
100
Chart Titlew(u)Matlab w(u)Excel 5 w(u)J-C
t(min) t dias Pindustrial (m) Pobs (m) DATOS A 1680 (km^2)1 0.0006944 2.2 Q 150 (l/s)2 0.0013889 5.5 t 96 hr3 0.0020833 8.21 Pbombeo r1 0.3048 m4 0.0027778 10.11 Pobs r2 100 m5 0.0034722 12.22 PNE 35 m6 0.0041667 13.31 Prof pozo 250 m8 0.0055556 16.11
10 0.0069444 17.921.804
15 0.0104167 22.120 0.0138889 25.0225 0.0173611 27.130 0.0208333 28.0540 0.0277778 30.0150 0.0347222 31.98 0.260 0.0416667 32.5 0.470 0.0486111 0.680 0.0555556 37.9 0.8590 0.0625 1
100 0.0694444 39.85 1.4120 0.0833333 40.5 1.95150 0.1041667 44 2.8200 0.1388889 47.2 4.2300 0.2083333 51 6.6400 0.2777778 54.8 8.55600 0.4166667 57.2 11.8800 0.5555556 61.4 14
1200 0.8333333 62.8 17.92000 1.3888889 67.8 22.63000 2.0833333 72.4 26.54000 2.7777778 75 296000 4.1666667 77.8 32.5
1 VERIFICAR LAS 3 CURVAS2. E EDITAR PARA HACER LA INTERPRETACION.
3 REGRESION DE LA CURVA EDITADA4 REALIZAR LA INVERSION
0.001 0.01 0.1 1 100
10
20
30
40
50
60
70
80
90
f(x) = 9.48065106280803 ln(x) + 65.173452328671R² = 0.997962450560393
Column C Logarithmic (Column C)
t(dias)
s(m
)
0 0.5 1 1.5 2 2.5 3 3.5 4 4.50
10
20
30
40
50
60
70
80
90
Column C
t(dias)
s(m
)
0.0001 0.001 0.01 0.1 1 101
10
100
log-log
Column C
t(dias)
s(m
)
0.0001 0.001 0.01 0.1 1 101
10
100
log-log
Column C
t(dias)
s(m
)
Resultados Jacob Cooper; Pbombeo Resultados Jacob Cooper; Pobs12960 m3/dia T= 108.7647 m2/dia T=
to= 0.001034 dias to=S= 2.723817 >1 S=
CREIBLE
215 mK= 0.505882 m/dia
RESULTADO ABSURDO!!!, S<1 SIEMPRE
λ=
T es la del pozo agricola porque no tiene efectos del bombeo.
0.001 0.01 0.1 1 100
10
20
30
40
50
60
70
80
90
f(x) = 9.48065106280803 ln(x) + 65.173452328671R² = 0.997962450560393
Column C Logarithmic (Column C)
t(dias)
s(m
)
0 0.5 1 1.5 2 2.5 3 3.5 4 4.50
10
20
30
40
50
60
70
80
90
Column C
t(dias)
s(m
)
0.0001 0.001 0.01 0.1 1 101
10
100
log-log
Column C
t(dias)
s(m
)
0 0.5 1 1.5 2 2.5 3 3.5 4 4.505
101520253035
18; 32.5
Curva completa Pobs Normal
Column D
t(dias
s(m
)
0.01 0.1 1 100
5
10
15
20
25
30
35
Completa semilog Pobs
0.01 0.1 1 100.1
1
10
100
18; 32.5
Curva completa Pobs log-log
Column D
t(dias
s(m
)
0.0001 0.001 0.01 0.1 1 101
10
100
log-log
Column C
t(dias)
s(m
)
0.01 0.1 1 100.1
1
10
100
18; 32.5
Curva completa Pobs log-log
Column D
t(dias
s(m
)
Resultados Jacob Cooper; Pobs120.2904 m2/dia0.098122 dias0.002656
CREIBLE
T es la del pozo agricola porque no tiene efectos del bombeo.
0 0.5 1 1.5 2 2.5 3 3.5 4 4.505
101520253035
18; 32.5
Curva completa Pobs Normal
Column D
t(dias
s(m
)
0.01 0.1 1 100
5
10
15
20
25
30
35
Completa semilog Pobs
0.1 1 100
5
10
15
20
25
30
35
f(x) = 8.57225476811601 ln(x) + 19.9006445890087R² = 0.99627120237779
Editada semilog Pobs
0.01 0.1 1 100.1
1
10
100
18; 32.5
Curva completa Pobs log-log
Column D
t(dias
s(m
)
0.01 0.1 1 100.1
1
10
100
18; 32.5
Curva completa Pobs log-log
Column D
t(dias
s(m
)
0.1 1 100
5
10
15
20
25
30
35
f(x) = 8.57225476811601 ln(x) + 19.9006445890087R² = 0.99627120237779
Editada semilog Pobs
A 1680Q 20 1.2 m^3/mint 1400
t' (min) t+t'/t' Ascenso(m)0 #DIV/0! 15.51 1401 13.33 467.6666666667 9.755 281 7.97 201 7.15
10 141 6.415 94.33333333333 5.620 71 5.230 47.66666666667 4.640 36 4.25 4.2550 29 3.9 3.960 24.33333333333 3.65 3.6580 18.5 3.3 3.3
100 15 3 3120 12.66666666667 2.7 2.7140 11 2.55 2.55160 9.75 2.4 2.4180 8.777777777778 2.25 2.25200 8 2.1 2.1250 6.6 1.8 1.8300 5.666666666667 1.65 1.65400 4.5 1.4 1.4
m 1.3862T 0.068888303170637 m^2/minT 99.1991565657175 m^3/dia
K 0.461391425887058 m/dia
Esta T es la mejor porque no tiene efectos de ruido.
0 200 400 600 800 1000 1200 1400 16000
2
4
6
8
10
12
14
Recuperación Normal
1 10 100 1000 100001
10
100
Recuperación log-log
1 10 100 1000 100000
2
4
6
8
10
12
14
f(x) = 1.38624384618541 ln(x) − 0.762222730844189R² = 0.998380773073523
Datos y regresion
Column C Column DLogarithmic (Column D)
1 10 100 1000 100000
2
4
6
8
10
12
14
f(x) = 1.38624384618541 ln(x) − 0.762222730844189R² = 0.998380773073523
Datos y regresion
Column C Column DLogarithmic (Column D)
0 200 400 600 800 1000 1200 1400 16000
2
4
6
8
10
12
14
Recuperación Normal
1 10 100 1000 100000
2
4
6
8
10
12
14
Recuperación Semilog
1 10 100 1000 100001
10
100
Recuperación log-log
1 10 100 1000 100000
2
4
6
8
10
12
14
f(x) = 1.38624384618541 ln(x) − 0.762222730844189R² = 0.998380773073523
Datos y regresion
Column C Column DLogarithmic (Column D)
1 10 100 1000 100000
2
4
6
8
10
12
14
f(x) = 1.38624384618541 ln(x) − 0.762222730844189R² = 0.998380773073523
Datos y regresion
Column C Column DLogarithmic (Column D)
1 10 100 1000 100000
2
4
6
8
10
12
14
Recuperación Semilog