Transcript Characterization of Aquifer Extent and Quality for Desalination and Brine Disposal Projects

Characterization of Aquifer Extent and
Quality for Desalination and Brine
Disposal Projects
Scerp Project : W-06- 4
Diane Doser, UTEP
Richard Langford, UTEP
Mark Baker, Geomedia Research and Development
Acknowledgements
• El Paso Water Utilities Cores, Logs
– Alfredo Ruiz
• Center for Environmental Resource
Management (CERM)
• Sarah Quinonez
• Sandy Marrufo
Project Goals
• Can use well logs as predictive tools in this and similar complex
settings.
– Correlate geophysical well logs with driller’s logs, core, cuttings, outcrop
exposures and surface geophysics
– Develop petrophysical relationships to predict important aquifer
properties including water salinity, and permeability
• Can we determine controls on the salinity within the aquifer.
– Determine the stratigraphy and lateral and vertical extent of facies
– The relationship of aquifers to faults, fractures, karsting (presence of
voids and fractures in limestone) and paleosols (ancient soils).
• Paleosols serve as important correlation units in otherwise complicated
alluvial (river) and lacustrine (lake) depositional systems, and may serve as
barriers to fluid flow
• Faults also serve as both barriers and conduits to fluid flow.
– Quantitatively estimate aquifer parameters and test which data are the
most reliable estimators.
Methods
• Two parallel research tracks
– Quantitative analysis of well logs using data
from cuttings
– Stratigraphic and sedimentologic
determination of stratigraphy and facies.
Locations of• wells
and
16 Wells drilled
by Elfaults
Paso Water Utilities (EPW
Hueco Bolson Aquifer
Wells are situated near
the a lateral boundary
between saline and
nonsaline parts of the
hueco bolson aquifer.
Water extracted from
the wells is used in the
El Paso
•
Purpose for drilling wells
– Supply brackish water for desalinization plant
• TDS from 976 to 1979 ppm
• Well cuttings and well logs on loan
– Create a trough in the ground water
• Protect fresh water aquifer from the saline aquifer
• Provides 40% of El Paso’ Water
From Sheng and Devere, 2005
From Sheng and Devere, 2005
Data Set
• Cuttings and logs from 16 wells (EPWU)
900-950 ft deep
• Well logs in digital format including
– gamma
– resistivity (16 and 64 inch normal and single
point)
– self potential
– Caliper
– temperature
Methods
• Grain Size Analysis Wells 601, 605, 610
• Stratigraphic correlation of all wells
• Interpretations of facies based on cuttings
(10 ft intervals) and logs.
• Log estimation of aquifer properties
Formation water salinity
• Three well logs used to estimate
– natural gamma ray
– Resistivity
– spontaneous potential (SP)
• To be quantitatively useful, the hole
diameter and drilling fluid salinity and
temperature need to be known
Estimation of Aquifer properties
from logs
1. Calculate water salinity from the SP log, drilling fluid resistivity, and
temperature logs.
2. Correct the resistivity log for borehole conditions.
3. Calculate clay content from averaged gamma ray and resistivity.
4. Calculate movable water content (effective porosity) for a simple
model assuming clay minerals, coarse-grained minerals, and free
pore water.
5. Calculate a mineral resistivity by taking water salinity from step 1,
and movable water content from step 3 to remove the effect of the
free pore water from the resistivity log.
6. Correlate the mineral resistivity to core-derived properties such as
surface area, average grain size, or simple grain-size distribution
models.
Examples of logs used in calculations
resistivity, ohm-m
API units (gamma), mV (SP)
40
35
30
25
20
15
10
5
0
650
150
125
100
75
50
25
0
650
660
660
680
680
690
690
700
700
710
depth, ft
710
depth, ft
720
720
730
730
740
740
750
760
760
ngam
SP
750
770
770
16
14
12
10
8
6
4
2
0
Shale baseline 730’-760’ in well 605
16in
64in
s.pt
670
670
single pt. resistivity, ohm-m
1. Calculate water salinity from the SP log, drilling fluid
resistivity, and temperature logs.
9
100
8
50
0
660
7
680
700
720
740
760
Rw ohm-m
SP mV
10
6
780
140
120
100
80
60
40
20
0
640
601 Depth
660
680
700
720
depth, ft
10
9.5
9
8.5
8
SP
7.5
Shale Baseline 7
6.5
Rw
6
740
760
780
Rw ohm-m
SP mV
depth, feet
2. Correct the resistivity log for borehole conditions Ct.
conductivity, mS/m
180
160
140
120
100
80
60
40
20
0
640
660
680
700
720
depth, ft
740
760
C16
C64
Ct
780
0.8
Vcl
120
0.7
Ct
100
0.6
Gamma Ray
80
0.5
60
0.4
40
0.3
20
0.2
0
0.1
-20
0
-40
640
660
680
700
720
depth, ft
740
760
780
API units (gamma), mS/m
(Ct)
Volume Clay (Vcl)
3. Calculate clay content from averaged gamma ray and
resistivity.
4. Calculate movable water content (effective porosity) for
a simple model assuming clay minerals, coarse-grained
minerals, and free pore water.
• Assumption of Max 20%, linearly occluded
by increasing clay percentage
• Vw = 0.20 * Vcl
Calculate a mineral resistivity
• √(Ct) = ( Vw) * √(Cw) + (1-Vw) * √(Cm)
• Mixing equation
Correlate the mineral resistivity to
core properties
• Complicated mixtures of sediment made
correlation difficult
• Surface area was most robust
2.5
est. surf. area (cuttings)
predict. surf. area (log)
surface area (m**2/gm)
2
1.5
1
0.5
0
0
20
40
60
80
mineral conductivity (mS/m)
100
120
605_601 Log-SA
2.5
Prediction from log
Calculated from core grain size
2
1.5
1
0.5
0
0
200
400
600
Depth ft
800
1000
Methods
• Log estimation of aquifer properties
• Sedimentologic and Stratigraphic Analysis
– Grain Size Analysis Wells 601, 605, 610
– Stratigraphic correlation of all wells
– Interpretations of facies based on cuttings (10
ft intervals)and logs.
Grain Size Analysis -- Mean and Standard Deviation proved insufficient
to differentiate facies, so the percentages of five classes were broken
out and input as log suites
Facies interpretations
• Facies 1. Gravels and coarse sands of mixed lithologies.
• Facies 2. Limestone and granite gravels. These are sediments
composed dominantly of gravels derived from the Franklin
Mountains. interpreted as gravels composing distal alluvial fans
extending from the front of the Franklin Mountains.
• Facies 3. Coarse grained sand with sparse 1-5 cm gravel clasts.
interpreted as deposits of distal alluvial fans.
• Facies 4. Silty sand and sandy silts with abundant soil carbonate
nodules. These are interpreted as floodplain and deltaic deposits,
formed where alluvial fan channels and streams flowing across the
Hueco Bolson fed into playa lakes.
• Facies 5. White sandy silt and silty sand. These are interpreted as
desert floor and playa lake margin deposits.
• Facies 6. Red and tan clays. interpreted as deposits of playa lake
beds.
samples from well 615
alluvial fan gravel
sieves and samples
sandy silt
Silt with carbonate nodules
Correlation of
facies
Stratigraphy shows layers offset by faults with
increasing movement with depth
Conclusions
• The resistivity log and grain size surface
area correlated best and should strongly
correlate with well production.
• Other measures were poor estimators
• The boundary between fresh and brackish
waters is a fault that localized playa lakes.
• Paleosols can be identified on faults and
may serve as correlation markers across
facies.
For the Future
• More wells to south to better define alongfault changes.
• Use of surface geophysics to define fault
locations and offsets
• Correlate corrected log data and delineate
changes in clay content permeability in the
subsurface.