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Estimation of Uniaxial Compaction Coefficient from GPS Measured Subsidence Dr.PARUL R. Patel Senior Associate Professor Nirma University, Ahmedabad by

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2 Organization of Presentation Introduction Introduction Objectives of the Study Objectives of the Study GPS Field Data Collection & Processing Methodology GPS Field Data Collection & Processing Methodology Analysis of Results Analysis of Results Estimation of Uniaxial Compaction Coefficient Estimation of Uniaxial Compaction Coefficient Conclusions Conclusions

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3 Land Subsidence Land subsidence is a gradual settling or sudden sinking of the earth's surface with or without horizontal movement Man-made Subsidence Occurs mainly due to Mining activities Mining activities Underground construction activities Underground construction activities Extraction of natural resources like water/gas/oil Extraction of natural resources like water/gas/oil

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4 Mechanism of Land Subsidence due to Gas Extraction Weight of overlying sediments partially supported by soil matrix and partially by gas/oil present in pores. Pressure p declines, and overburden load transferred to soil matrix. Compaction takes place if soil is compressible Bowl-shaped depression appears with large displacement at centre.

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5 Effects of Land Subsidence Effects of Land Subsidence Changes in Elevation and Slope of Canals, Drains, Pipe lines etc Changes in Elevation and Slope of Canals, Drains, Pipe lines etc Damage to Infrastructure Damage to Infrastructure Failure of Well Casings Failure of Well Casings Water Intrusion in Coastal Areas Water Intrusion in Coastal Areas Reduction in Permeability, Loss of Hydrocarbon Reduction in Permeability, Loss of Hydrocarbon productivity productivity Fault Reactivation Resulting in Seismic Activity Fault Reactivation Resulting in Seismic Activity Development of Fissures and Sinkholes Development of Fissures and Sinkholes Even Settlement rarely causes any problems but uneven settlement creates problems

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6 Objectives of the Study Use of GPS technique to monitor subsidence using a case study near Olpad Region, Surat, Gujarat To identify and study effects of parameters responsible for land subsidence, like, pressure depletion, gas extraction, water level, Uniaxial Compaction Coefficient, Reservoir dimensions Calculation of Uniaxial Compaction Coefficient

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7 Ekofisk Oil Field, ,Ekofisk Oil Field, , Single Frequency Novtel, Novtel Software used Groningen Gas Field, ,Groningen Gas Field, , Dual Frequency, Bernese Software Coachella Valley, California, , Dual Frequency, GP Survey SoftwareCoachella Valley, California, , Dual Frequency, GP Survey Software Rafsanjan Plain, Iran, ,Rafsanjan Plain, Iran, , Leika, SKIPro Software Ojiya City, Japan, ,Ojiya City, Japan, , Dual Frequency, Bernese Software Jakarta, Indonesia, , Dual Frequency, Bernese SoftwareJakarta, Indonesia, , Dual Frequency, Bernese Software GPS used for Monitoring Subsidence

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8 Reference Network & Monitoring Stations with Reservoir Boundary Locations of IGS Stations Deformation Stations with Reference Stations Deformation Stations and Presumed Reservoir Boundary Details of the Study Area

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9 GPS Monument at Monitoring Station C/S of GPS Monument GPS Monument 4000 ssi Receiver with Choke Ring Antenna

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10 Processing Parameters and Methodology IGS stations tightly constrained, to get coordinates of all the four reference stations and IITB permanent reference station. IGS stations tightly constrained, to get coordinates of all the four reference stations and IITB permanent reference station. Coordinates of all 27-deformation stations were processed with two reference stations and IITB station by tightly constraining them. Coordinates of all 27-deformation stations were processed with two reference stations and IITB station by tightly constraining them. Processing Mode Software : Post Processing Mode : Bernese V4.2 Types of orbit: Precise Ephemeris (SP3) IGS stations: LHAS,BAHR,IISC(ITRF-2000) Ionospheric Correction : Differential Correction and combining L1 & L2 frequencies Tropospheric correction PDOP Angle of Elevation : SAASTAMOINEN Model (Hugentobler & Satirapod) & site specific piecewise linear method : 4 - for better Satellite Geometry (Rabbany, 2002) : 15° (to avoid signals from lower satellites to reduce tropospheric error)

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11 Average Effective Subsidence for May Campaigns Campaigns May 04 - May 05 - May 06 - March 07 May 04 - March 07 Av. Effective Subsidence within Reservoir Boundary (mm) 29 ± 525 ± 532 ± 586 ± 5 Rate of Subsidence 30 mm/year within Reservoir Boundary

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12 Study of Reservoir Pressure and its behaviour Maximum Pressure Depleted on north side More Numbers of Gas Wells Located on North side Maximum Subsidence observed on North side May 2004June 2007 Max. Pressure: 2290 kN/m 2 at NSA4 Min. Pressure : 2034 kN/m 2 at NSA2 Av. pressure of the reservoir: 2105 kN /m 2 Max Pressure: 1336 kN/m 2 at NSA2 Min. Pressure: 989 kN/m 2 at NSA1 Av. pressure of the reservoir: 1098 kN/m 2

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13 Relation Between Gas Extraction and Pressure Depletion Months Cumulative Gas Extraction (m 3 ) Average Gas Pressure (kN/m 2 ) May December May December May December June Linear relation Between Gas Extraction & Average Pressure Pressure is Depleting Continuously with increase in Cumulative Gas Extraction

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14 Relation between Cumulative Effective Subsidence & Cumulative Gas Extraction Gas Extraction is the major cause of Subsidence over the Study area Correlation Coefficient is Found to be High 0.83 Linear Relationship is observed to be Suitable with Regression Analysis CampaignsCumulative Gas Extraction (m 3 ) from four gas wells Average Effective Subsidence (∆s) for four stations May.04 - Oct E May.04 - Feb E+072 May.04 - May E May.04 - Octo.051.3E May.04 - Jan E May.04 - Mar E May.04 - May E May.04 - Oct E May.04 - Jan E May.04 - Mar.072.7E+08-91

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15 Relation between Water Level and Subsidence Change in Water Level (Four Wells)Change in Ellipsoidal Height (Four Wells) No permanent water depletion observed Net reduction in the average Ellipsoidal Height Seasonal Change Observed in Water Level and in Ellipsoidal Height

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16 Estimation of Uniaxial Compaction Coefficient (C m ) Laboratory Measured C m C m = 2.7E-05 m 2 /kN Where, Modulus of Elasticity (E) =2.5E04 kN/m 2 (Laboratory Measured) And Poisson’s Ratio ( υ) = 0.33 Laboratory Measured C m Value usually overestimated Subsidence = C m H Δp Subsidence = 953 mm For (Δp = 905 kN/m 2, H=39 m) Subsidence Very High Compared to Measured Subsidence (86 mm)

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17 Average C m for Four Wells ∆s = (-1.84E-06) (∆p * H) R = 0.73 C m values Ranging from 1.27E-06 m 2 /kN to 3.70E-06 m 2 /kN Average C m Value is 1.84E-06 m 2 /kN C m = 1.84E-06 m 2 /kN For Barbara Field, Field Measured C m Values were 2 x to 5 x m 2 /kN Laboratory Measured C m values ranging from 1 x to 5 x m 2 /kN Laboratory Measured C m is more than ten times to Field Measured C m with GPS

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18 Subsidence Prediction based on C m Calculated using Nucleus of Strain Method (Geertsma, 1978) (Assuming Reservoir Compaction ≠ Subsidence) Subsidence at the Centre of the Reservoir Value of ‘A’ depends on two Dimensionless ratios η=D/R and ρ = r/R D is the Depth of Burial (175 m), R is radius of Reservoir (2500 m), r is the distance of point from centre of the Reservoir (r=0) This C m value used to predict subsidence from time to time over this reservoir

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19 Effective subsidence over the study area was 86 mm during February 2004 to March 2007 within reservoir boundary Subsidence is directly related to the amount of gas extracted and resulting pressure. A linear relationships are observed between: Cumulative gas extraction and average reservoir pressure (R =0.99) Subsidence and gas extraction ( R = 0.83) subsidence and pressure depletion ( R = to 0.82) The average compaction coefficient C determined from GPS studies (assuming subsidence = compaction) is found to be 1.84E-06 m 2 /kN. The average compaction coefficient C m determined from GPS studies (assuming subsidence = compaction) is found to be 1.84E-06 m 2 /kN. Subsidence prediction based on field measured is more acceptable than the laboratory measured uniaxial compaction coefficient, as it is always higher by one order of magnitude than the actual measured subsidence in the field. Estimating C m (assuming subsidence = compaction) based on GPS measured parameters and Nucleus of Strain Method is found to be 1.95E- 06 m 2 /kN. Conclusions

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21 Subsidence Predicted by Taurus (2003) Reservoir Thickness = 30 m; Duration 17 years Reservoir Thickness = 30 m Subsidence measured with GPS May, 2004 to March 2007 Pressure Depletion = 1000 kN/m 2 Pressure Depletion = 1200 kN/m 2 Actual pressure depletion of 905 kN/m 2 (Darcy, 2006 ) Linear Compressibility Non linear Compressibil ity Full –Field Reservoir model and realistic depletion strategy, FEM used Based on Linear Compressibility 809 mm720 mm610 mm733 mm86 mm

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22 Subsidence Predicted by Taurus (2003) Reservoir Thickness = 30 m; Duration 17 years Based on Linear Compressibility, H = 30 m and actual pressure depletion of 905 kN/m 2 (Darcy, 2006 ) Subsidence measured with GPS May, 2004 to March 2007 Pressure Depletion = 1000 kN/m 2 Pressure Depletion = 1200 kN/m 2 Linear Compressibility Non linear Compressibility Full –Field Reservoir model and realistic depletion strategy, FEM used 809 mm 720 mm610 mm 733 mm86 mm

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23 Subsidence Predicted by Taurus (2003) Reservoir Thickness = 30 m; Duration 17 years Reservoir Thickness = 30 m Subsidence measured with GPS May, 2004 to March 2007 Pressure Depletion = 1000 kN/m 2 Pressure Depletion = 1200 kN/m 2 Actual pressure depletion of 905 kN/m 2 (Darcy, 2006 ) Linear Compressibility Non linear Compressibil ity Full –Field Reservoir model and realistic depletion strategy, FEM used Based on Linear Compressibility 809 mm720 mm610 mm733 mm86 mm

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