Nuclear Magnetic Resonance (NMR):

Transcription

1 Nuclear Magnetic Resonance (): An Emerging for Aquifer Characterization in Water Resource Applications Presented by: Lauren Handley, R.G. Senior Hydrogeologist 1

2 for Water Resource Applications Production and Recharge Well Design Can technology assist water managers in Productivity/Injection Estimates assessing an aquifer for Water Resource Groundwater Recharge investigations? Assessments Groundwater Model Calibration A critical component of all these water resource applications is AQUIFER YIELD. How much MOBILE water is available? How does the permeability vary throughout the aquifer? 2

3 History 1940 s and 50 s - phenome has been recognized Oil and Gas industry conducing research Chevron developed first NML tool utilizing the earth s magnetic field Atlas (Baker) introduced a tool based on Chevron s centralized design Schlumberger had made a pad type tool of their own design. 1970s -Magnetic Resonance Imaging (MRI) was developed for medicine. 1990s - Modern pulse-echo logging tools: Vista Clara introduced slim hole Javelin based on MRIL design. 3

4 Permanent magnets in probe polarize hydrogen in H 2 O molecules Induction coil in probe transmits RF pulses to excite and measure signal signal is generated and detected only within a thin cylindrical sensitive volume surrounding the center of the tool Diameter of sensitive shell changes with operating frequency Typically 2+ shells are logged simultaneously to provide radial sensitivity Borehole diameter is an important factor H 2 O 4

5 Physics Magnets polarize hydrogen spins creating a nuclear magnetization Pulsed RF field excites hydrogen magnetization away from static field Hydrogen precess about static field (signal) and return to equilibrium Relaxation Signal Static Field Pulsed Field 5

6 Hydrologic Properties from Signal S 0 φφ T 2 pore size Provides Water Content Porosity (Lithology Independent) Pore Size (Volume/Surface Area) 6

7 Hydrologic Properties from TT 2 pppppppp ssssssss bound mobile bound φφ NNNNNN TT 2 rr pppppppp T 2 Distribution mobile T 2 Distribution KK KKKK = φφrr2 pppppppp KK ττ KKKK = φφ rr 2 pppppppp KK? = φφ NNNNNNNNNNNNNN 2 ττ ττ KK? = φφ 2 NNNNNN TT 2 ττ aa TTaa TT 2 KK NNNNNN KK NNNNNN = bbbb= NNNNNN bbφφ NNNNNN Provides Water Content Porosity (Lithology Independent) Pore Size (Volume/Surface Area) Pore Size V/S Distribution Bound versus Mobile Water Hydraulic Conductivity 7

8 Output T 2 Distribution Permeability Bound versus Mobile Water Content 8

9 Method: Logging Electrical resistivity, sonic, density, gamma, and neutron logs Flow meter surveys (spinner logs) in completed wells Sand and Gravel Sandy Clay Clayey Sand Gravel Silty Sand Clay 9

10 Method: Hydrologic Testing Falling head or slug tests in boreholes Aquifer tests in completed wells A volume of water is added, & the water-level change is recorded 10

11 Method: Results There is a need for more quantitative methods. GAMMA E-LOG GUARD FLUORIDE mg/l NITRATE mg/l TDS mg/l GEOPHYSICAL LOGS GROUNDWATER QUALITY GEOLOGY 11

12 Geophysical Measurements Provide: Can Direct Measurement technology of assist Water water Content providers and Porosity and managers Direct Imaging assessing of the an Pore aquifer Size Distribution for Water Resource Estimation of Bound investigations? and Mobile Water Fractions Estimation of Hydraulic Conductivity and Transmissivity Hydrogeologic Properties are Directly Characterized 12

13 Case Studies and Take Aways Denver Water ASR Pilot Study (CO) Town of Castle Rock Well (CO) City of Phoenix ASR Well (AZ) 13

14 Denver Water ASR Pilot Study Logging Objective: characterize Denver basin aquifer properties, especially hydraulic conductivity, for potential aquifer storage and recovery. 14

15 Denver Water ASR Exploratory Borings Location A Location B 15

16 Denver Water Take Away Able to correlate units between boreholes using? Calibration constants are key to deriving K? Would like to compare this data with actual pumping test values More work to be done 16

17 Castle Rock Well 2 Filter interval : 72 ft 2 /day Constant Rate Test Transmissivity 70 ft 2 /day Screen interval : 65 ft 2 /day 17

18 Castle Rock Well Take Away and aquifer test results correlate for filter-pack/screen interval Productivity estimates/screen design based on alone may have been yielded positive results? Would like to compare this data to not only aquifer tests, but also to various depths in the borehole (i.e. slug tests) 18

19 Phoenix ASR Well 19

20 Phoenix ASR Well Productivity Estimates Using Falling Head Test Zone # Depth, feet Depth Interval, feet Aqtesolv K-value, ft/d Applied Zone Interval, feet Calculated T-value, gpd/ft Estimated SC, gpm/ft Estimated capacity at 100 ft drawdown, gpm Zone Zone Zone Zone Zone Zone Zone SWL 807 Estimated Total Production Rate, gpm 335 Empirical Equation Slug Test K-values T = Kb T (gpm/ft) 1,500 where: Q = gpm; T = gpd/ft; s = feet of drawdown = Q/s Slug Test Estimated Productivity: 335 gpm with 100 ft of Drawdown 20

21 Phoenix ASR Well Productivity Estimates using Zone # Depth, feet K- value, ft/d Applied Zone Interval, feet Calculated T- value, gpd/ft *Estimated SC, gpm/ft Estimated Capacity at 100 feet Drawdown, gpm Zone Zone Zone Zone Zone Zone Zone Zone Zone Zone Zone Zone Zone Zone Zone Zone Zone Zone Zone Zone Zone Zone Zone Zone Zone SWL Estimated Total Production Rate, gpm 870 Filter Pack Interval Zone Estimated Productivity: 870 gpm with 100 ft of Drawdown 21

22 Phoenix ASR Well Slug Test Estimated Productivity: 335 gpm 100 ft of Drawdown Zones Estimated Productivity: 870 gpm 100 ft of Drawdown Aquifer Test Productivity: 1,095 gpm 100 ft of Drawdown 22

23 Phoenix ASR Well Take Away Significant underestimation of hydraulic conductivity from slug tests Fill in gaps in hydraulic conductivity rather than extrapolation (i.e. using data)? Zone construction constraints contributed to lack of zone development? Projecting underestimated K- values exacerbates the problem (i.e. underestimated productivity) More work to be done 23

24 s Benefits Direct detection and quantification of water content and porosity Determination of bound versus unbound water Quantitative estimates of hydraulic conductivity, transmissivity, specific yield, and pore-size distribution Challenges Confidence of dataset Overall cost savings or cost increase? Borehole diameter limitations Requires pre-project planning to ensure limitations are understood, adequate data is collected, proper constants are applied for data processing 24

25 Questions? Special thanks to: Elliot Grunewald, Vista Clara, Inc. Dave Colvin, Leonard Rice Engineers, Inc. Town Castle Rock City of Phoenix Denver Water 25