scholarly journals Application of time-lapse ERT imaging to watershed characterization

Geophysics ◽  
2008 ◽  
Vol 73 (3) ◽  
pp. G7-G17 ◽  
Author(s):  
Carlyle R. Miller ◽  
Partha S. Routh ◽  
Troy R. Brosten ◽  
James P. McNamara
Keyword(s):  
Reference Model ◽  
Time Lapse ◽  
Data Sets ◽  
Data Set ◽  
Resistivity Tomography ◽  
Practical Applications ◽  
Data Inversion ◽  
Time Periods ◽  
The Difference ◽  
Base Data

Time-lapse electrical resistivity tomography (ERT) has many practical applications to the study of subsurface properties and processes. When inverting time-lapse ERT data, it is useful to proceed beyond straightforward inversion of data differences and take advantage of the time-lapse nature of the data. We assess various approaches for inverting and interpreting time-lapse ERT data and determine that two approaches work well. The first approach is model subtraction after separate inversion of the data from two time periods, and the second approach is to use the inverted model from a base data set as the reference model or prior information for subsequent time periods. We prefer this second approach. Data inversion methodology should be consideredwhen designing data acquisition; i.e., to utilize the second approach, it is important to collect one or more data sets for which the bulk of the subsurface is in a background or relatively unperturbed state. A third and commonly used approach to time-lapse inversion, inverting the difference between two data sets, localizes the regions of the model in which change has occurred; however, varying noise levels between the two data sets can be problematic. To further assess the various time-lapse inversion approaches, we acquired field data from a catchment within the Dry Creek Experimental Watershed near Boise, Idaho, U.S.A. We combined the complimentary information from individual static ERT inversions, time-lapse ERT images, and available hydrologic data in a robust interpretation scheme to aid in quantifying seasonal variations in subsurface moisture content.

Common-focus point-based target-oriented imaging approach for continuous seismic reservoir monitoring

Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. M41-M48 ◽  
Author(s):  
Hongwei Liu ◽  
Mustafa Naser Al-Ali
Keyword(s):  
Seismic Data ◽  
Rock Physics ◽  
Time Lapse ◽  
Velocity Estimation ◽  
Estimation Methods ◽  
Data Sets ◽  
Data Set ◽  
Velocity Models ◽  
Reservoir Monitoring ◽  
Focus Point

The ideal approach for continuous reservoir monitoring allows generation of fast and accurate images to cope with the massive data sets acquired for such a task. Conventionally, rigorous depth-oriented velocity-estimation methods are performed to produce sufficiently accurate velocity models. Unlike the traditional way, the target-oriented imaging technology based on the common-focus point (CFP) theory can be an alternative for continuous reservoir monitoring. The solution is based on a robust data-driven iterative operator updating strategy without deriving a detailed velocity model. The same focusing operator is applied on successive 3D seismic data sets for the first time to generate efficient and accurate 4D target-oriented seismic stacked images from time-lapse field seismic data sets acquired in a [Formula: see text] injection project in Saudi Arabia. Using the focusing operator, target-oriented prestack angle domain common-image gathers (ADCIGs) could be derived to perform amplitude-versus-angle analysis. To preserve the amplitude information in the ADCIGs, an amplitude-balancing factor is applied by embedding a synthetic data set using the real acquisition geometry to remove the geometry imprint artifact. Applying the CFP-based target-oriented imaging to time-lapse data sets revealed changes at the reservoir level in the poststack and prestack time-lapse signals, which is consistent with the [Formula: see text] injection history and rock physics.

A Ccomparison of sedigraph and pipette methods for soil particle-size analysis

Soil Research ◽  
1993 ◽  
Vol 31 (4) ◽  
pp. 407 ◽  
Author(s):  
GD Buchan ◽  
KS Grewal ◽  
JJ Claydon ◽  
RJ Mcpherson
Keyword(s):  
Particle Size ◽  
New Zealand ◽  
Particle Size Analysis ◽  
Size Analysis ◽  
Data Sets ◽  
Regression Equations ◽  
Total Iron Content ◽  
Data Set ◽  
X Ray ◽  
The Difference

The X-ray attenuation (Sedigraph) method for particle-size analysis is known to consistently estimate a finer size distribution than the pipette method. The objectives of this study were to compare the two methods, and to explore the reasons for their divergence. The methods are compared using two data sets from measurements made independently in two New Zealand laboratories, on two different sets of New Zealand soils, covering a range of textures and parent materials. The Sedigraph method gave systematically greater mass percentages at the four measurement diameters (20, 10, 5 and 2 �m). For one data set, the difference between clay (<2 �m) percentages from the two methods is shown to be positively correlated (R2 = 0.625) with total iron content of the sample, for all but one of the soils. This supports a novel hypothesis that the typically greater concentration of Fe (a strong X-ray absorber) in smaller size fractions is the major factor causing the difference. Regression equations are presented for converting the Sedigraph data to their pipette equivalents.

How to Borrow Information From Unlinked Data? A Relative Density Approach for Predicting Unobserved Distributions

2020 ◽  
pp. 004912412092621
Author(s):  
Siwei Cheng
Keyword(s):  
Relative Density ◽  
Wage Inequality ◽  
Methodological Approach ◽  
Data Sets ◽  
Social Scientists ◽  
Multiple Data ◽  
Multiple Data Sets ◽  
The Difference ◽  
Combine Information ◽  
Base Data

One of the most important developments in the current era of social sciences is the growing availability and diversity of data, big and small. Social scientists increasingly combine information from multiple data sets in their research. While conducting statistical analyses with linked data is relatively straightforward, borrowing information across unlinked data can be much more challenging due to the absence of unit-to-unit linkages. This article proposes a new methodological approach for borrowing information across unlinked surveys to predict unobserved distributions. The gist of the proposed approach lies in the idea of using the relative density between the observed and unobserved distributions in the reference data to characterize the difference between the two distributions and borrow that information to the base data. Relying on the assumption that the relative density between the observed and unobserved distributions is similar between data sets, the proposed relative density approach has the key advantage of allowing the researcher to borrow information about the shape of the distribution, rather than a few summary statistics. The approach also comes with a method for incorporating and quantifying the uncertainty in its output. We illustrate the formulation of this approach, demonstrate with simulation examples, and finally apply it to address the problem of employment selection in wage inequality research.

Defusing Technology:Technology Diffusion in British Columbia

1993 ◽  
Vol 9 (1) ◽  
pp. 46-61 ◽  
Author(s):  
Arminée Kazanjian ◽  
Kathryn Friesen
Keyword(s):  
British Columbia ◽  
Historical Data ◽  
Current Data ◽  
Fiscal Year ◽  
Data Sets ◽  
Canadian Province ◽  
Data Set ◽  
Time Periods ◽  
Institutional Profile ◽  
Areas Of Interest

AbstractIn order to explore the diffusion of the selected technologies in one Canadian province (British Columbia), two administrative data sets were analyzed. The data included over 40 million payment records for each fiscal year on medical services provided to British Columbia residents (2,968,769 in 1988) and information on physical facilities, services, and personnel from 138 hospitals in the province. Three specific time periods were examined in each data set, starting with 1979–80 and ending with the most current data available at the time. The detailed retrospective analysis of laboratory and imaging technologies provides historical data in three areas of interest: (a) patterns of diffusion and volume of utilization, (b) institutional profile, and (c) provider profile. The framework for the analysis focused, where possible, on the examination of determinants of diffusion that may be amenable to policy influence.

scholarly journals Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns

2018 ◽  
Vol 18 (3) ◽  
pp. 1573-1592 ◽  
Author(s):  
Gerrit de Leeuw ◽  
Larisa Sogacheva ◽  
Edith Rodriguez ◽  
Konstantinos Kourtidis ◽  
Aristeidis K. Georgoulias ◽  
...  
Keyword(s):  
Time Series ◽  
European Space Agency ◽  
Mainland China ◽  
Satellite Observations ◽  
Data Sets ◽  
Data Set ◽  
Modis Aod ◽  
The Difference ◽  
Along Track ◽  
Aerosol Properties

Abstract. The retrieval of aerosol properties from satellite observations provides their spatial distribution over a wide area in cloud-free conditions. As such, they complement ground-based measurements by providing information over sparsely instrumented areas, albeit that significant differences may exist in both the type of information obtained and the temporal information from satellite and ground-based observations. In this paper, information from different types of satellite-based instruments is used to provide a 3-D climatology of aerosol properties over mainland China, i.e., vertical profiles of extinction coefficients from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), a lidar flying aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite and the column-integrated extinction (aerosol optical depth – AOD) available from three radiometers: the European Space Agency (ESA)'s Along-Track Scanning Radiometer version 2 (ATSR-2), Advanced Along-Track Scanning Radiometer (AATSR) (together referred to as ATSR) and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite, together spanning the period 1995–2015. AOD data are retrieved from ATSR using the ATSR dual view (ADV) v2.31 algorithm, while for MODIS Collection 6 (C6) the AOD data set is used that was obtained from merging the AODs obtained from the dark target (DT) and deep blue (DB) algorithms, further referred to as the DTDB merged AOD product. These data sets are validated and differences are compared using Aerosol Robotic Network (AERONET) version 2 L2.0 AOD data as reference. The results show that, over China, ATSR slightly underestimates the AOD and MODIS slightly overestimates the AOD. Consequently, ATSR AOD is overall lower than that from MODIS, and the difference increases with increasing AOD. The comparison also shows that neither of the ATSR and MODIS AOD data sets is better than the other one everywhere. However, ATSR ADV has limitations over bright surfaces which the MODIS DB was designed for. To allow for comparison of MODIS C6 results with previous analyses where MODIS Collection 5.1 (C5.1) data were used, also the difference between the C6 and C5.1 merged DTDB data sets from MODIS/Terra over China is briefly discussed. The AOD data sets show strong seasonal differences and the seasonal features vary with latitude and longitude across China. Two-decadal AOD time series, averaged over all of mainland China, are presented and briefly discussed. Using the 17 years of ATSR data as the basis and MODIS/Terra to follow the temporal evolution in recent years when the environmental satellite Envisat was lost requires a comparison of the data sets for the overlapping period to show their complementarity. ATSR precedes the MODIS time series between 1995 and 2000 and shows a distinct increase in the AOD over this period. The two data series show similar variations during the overlapping period between 2000 and 2011, with minima and maxima in the same years. MODIS extends this time series beyond the end of the Envisat period in 2012, showing decreasing AOD.

scholarly journals Evaluative application of UKCP09‐based downscaled future weather years to simulate overheating risk in typical English homes

2013 ◽  
Vol 31 (4) ◽  
pp. 231-252 ◽  
Author(s):  
Rajat Gupta ◽  
Matthew Gregg ◽  
Hu Du ◽  
Katie Williams
Keyword(s):  
Climate Change ◽  
Simulation Modelling ◽  
Simulation Software ◽  
Building Simulation ◽  
Future Research ◽  
Climate Projections ◽  
Data Sets ◽  
Data Set ◽  
Content Type ◽  
The Difference

PurposeTo critically compare three future weather year (FWY) downscaling approaches, based on the 2009 UK Climate Projections, used for climate change impact and adaptation analysis in building simulation software.Design/methodology/approachThe validity of these FWYs is assessed through dynamic building simulation modelling to project future overheating risk in typical English homes in 2050s and 2080s.FindingsThe modelling results show that the variation in overheating projections is far too significant to consider the tested FWY data sets equally suitable for the task.Research and practical implicationsIt is recommended that future research should consider harmonisation of the downscaling approaches so as to generate a unified data set of FWYs to be used for a given location and climate projection. If FWY are to be used in practice, live projects will need viable and reliable FWY on which to base their adaptation decisions. The difference between the data sets tested could potentially lead to different adaptation priorities specifically with regard to time series and adaptation phasing through the life of a building.Originality/valueThe paper investigates the different results derived from FWY application to building simulation. The outcome and implications are important considerations for research and practice involved in FWY data use in building simulation intended for climate change adaptation modelling.

scholarly journals A shallow geothermal experiment in a sandy aquifer monitored using electric resistivity tomography

Geophysics ◽  
2012 ◽  
Vol 77 (1) ◽  
pp. B11-B21 ◽  
Author(s):  
Thomas Hermans ◽  
Alexander Vandenbohede ◽  
Luc Lebbe ◽  
Frédéric Nguyen
Keyword(s):  
Transport Model ◽  
Groundwater Resources ◽  
Time Lapse ◽  
Electric Resistivity ◽  
Geothermal Systems ◽  
Resistivity Tomography ◽  
Temperature Changes ◽  
Practical Applications ◽  
Heated Water ◽  
Sandy Aquifer

Groundwater resources are increasingly used around the world for geothermal exploitation systems. To monitor such systems and to estimate their governing parameters, we rely mainly on borehole observations of the temperature field at a few locations. Bulk electric resistivity variations can bring important information on temperature changes in aquifers. We have used surface electric resistivity tomography to monitor spatially temperature variations in a sandy aquifer during a thermal injection test. Heated water (48°C) was injected for 70 hours at the rate of [Formula: see text] in a 10.5°C aquifer. Temperature changes derived from time-lapse electric images were in agreement with laboratory water electric conductivity-temperature measurements. In parallel, a coupled hydrogeologic saturated flow and heat transport model was calibrated on geophysical data for the conceptual model, and on hydrogeologic and temperature data for the parameters. The resistivity images showed an upper flow of heated water along the well above the injection screens and led to a new conceptualization of the hydrogeologic source term. The comparison between the temperature models derived from resistivity images and from the simulations was satisfactory. Quantitatively, resistivity changes allowed estimating temperature changes within the aquifer, and qualitatively, the heated plume evolution was successfully monitored. This work demonstrates the ability of electric resistivity tomography to study heat and storage experiments in shallow aquifers. These results could potentially lead to a number of practical applications, such as the monitoring or the design of shallow geothermal systems.

Angle-domain common-image gathers from anisotropic migration

Geophysics ◽  
2007 ◽  
Vol 72 (2) ◽  
pp. S81-S91 ◽  
Author(s):  
Biondo Biondi
Keyword(s):  
Complex I ◽  
Theoretical Development ◽  
Isotropic Case ◽  
Data Set ◽  
Practical Applications ◽  
Wavefield Continuation ◽  
The Difference ◽  
Contrast Group ◽  
Vti Media ◽  
The Relationship

I present a general methodology for computing angle-domain common-image gathers (ADCIGs) in conjunction with anisotropic wavefield-continuation migration. The method is based on transforming the prestack image from the subsurface-offset domain to the angle domain using slant stacks. The processing sequence is the same as that for computing ADCIGs for the isotropic case, though the interpretation of the relationship between the slopes measured in the prestack image and the aperture angles is more complex. I demonstrate that the slopes measured by performing slant stacks along the subsurface-offset axis of the prestack image provide a good approximation of the phase aperture angles, and they are exactly equal to the phase aperture angles for flat reflectors in vertical transversly isotropic (VTI) media. In the general case of dipping reflectors, the angles computed using slant stacks can be easily corrected by applying the relationships that I present in this paper, and the accurate aperture angles can be determined as a function of the reflector dip and anisotropic slowness at the reflector. I derive these relationships from both plane-wave and ray viewpoints. This theoretical development links the kinematics in ADCIGs with migration-velocity errors. I apply the proposed method to compute ADCIGs from the prestack image obtained by anisotropic migration of a 2D line recorded in the Gulf of Mexico. I analyze the error introduced by neglecting the difference between the true phase aperture angle and the angle computed through slant stacks, showing that, at least for this data set, these errors are negligible and can be safely ignored. In contrast, group aperture angles can be quite different from phase aperture angles; thus, ignoring the distinction between these two angles can be detrimental to practical applications.

scholarly journals SCIAMACHY WFM-DOAS XCO<sub>2</sub>: comparison with CarbonTracker XCO<sub>2</sub> focusing on aerosols and thin clouds

2012 ◽  
Vol 5 (2) ◽  
pp. 2887-2931 ◽  
Author(s):  
J. Heymann ◽  
O. Schneising ◽  
M. Reuter ◽  
M. Buchwitz ◽  
V. V. Rozanov ◽  
...  
Keyword(s):  
Southern Hemisphere ◽  
Temporal Correlation ◽  
Anthropogenic Activity ◽  
Data Sets ◽  
Spatial Correlations ◽  
Data Set ◽  
Cloud Data ◽  
Temporal Correlations ◽  
Retrieval Errors ◽  
The Difference

Abstract. Carbon dioxide (CO2) is the most important greenhouse gas whose atmospheric loading has been significantly increased by anthropogenic activity leading to global warming. Accurate measurements and models are needed in order to reliably predict our future climate. This, however, has challenging requirements. Errors in measurements and models need to be identified and minimised. In this context, we present a comparison between satellite-derived column-averaged dry air mole fractions of CO2, denoted XCO2, retrieved from SCIAMACHY/ENVISAT using the WFM-DOAS algorithm, and output from NOAA's global CO2 modelling and assimilation system CarbonTracker. We investigate to what extent differences between these two data sets are influenced by systematic retrieval errors due to aerosols and unaccounted clouds. We analyse seven years of SCIAMACHY WFM-DOAS version 2.1 retrievals (WFMDv2.1) using the latest version of CarbonTracker (version 2010). We investigate to what extent the difference between SCIAMACHY and CarbonTracker XCO2 are temporally and spatially correlated with global aerosol and cloud data sets. For this purpose, we use a global aerosol data set generated within the European GEMS project, which is based on assimilated MODIS satellite data. For clouds, we use a data set derived from CALIOP/CALIPSO. We find significant correlations of the SCIAMACHY minus CarbonTracker XCO2 difference with thin clouds over the Southern Hemisphere. The maximum temporal correlation we find for Darwin, Australia (r2 = 54%). Large temporal correlations with thin clouds are also observed over other regions of the Southern Hemisphere (e.g. 43% for South America and 31% for South Africa). Over the Northern Hemisphere the temporal correlations are typically much lower. An exception is India, where large temporal correlations with clouds and aerosols have also been found. For all other regions the temporal correlations with aerosol are typically low. For the spatial correlations the picture is less clear. They are typically low for both aerosols and clouds, but dependent on region and season, they may exceed 30% (the maximum value of 46% has been found for Darwin during September to November). Overall we find that the presence of thin clouds can potentially explain a significant fraction of the difference between SCIAMACHY WFMDv2.1 XCO2 and CarbonTracker over the Southern Hemisphere. Aerosols appear to be less of a problem. Our study indicates that the quality of the satellite derived XCO2 will significantly benefit from a reduction of scattering related retrieval errors at least for the Southern Hemisphere.

scholarly journals The SPARC water vapour assessment II: Comparison of stratospheric and lower mesospheric water vapour time series observed from satellites

2018 ◽  
Author(s):  
Farahnaz Khosrawi ◽  
Stefan Lossow ◽  
Gabriele P. Stiller ◽  
Karen H. Rosenlof ◽  
Joachim Urban ◽  
...  
Keyword(s):  
Time Series ◽  
Water Vapour ◽  
Data Sets ◽  
Data Set ◽  
The Future ◽  
Modelling Studies ◽  
The Difference ◽  
The Tropics ◽  
The Antarctic ◽  
Satellite Instruments

Abstract. Time series of stratospheric and lower mesospheric water vapour using 33 data sets from 15 different satellite instruments were compared in the framework of the second SPARC (Stratosphere-troposphere Processes And their Role in Climate) water vapour assessment (WAVAS-II). This comparison aimed to provide a comprehensive overview of the typical uncertainties in the observational database that can be considered in the future in observational and modelling studies addressing e.g stratospheric water vapour trends. The time series comparisons are presented for the three latitude bands, the Antarctic (80°–70° S), the tropics (15° S–15° N) and the northern hemisphere mid-latitudes (50° N–60° N) at four different altitudes (0.1, 3, 10 and 80 hPa) covering the stratosphere and lower mesosphere. The combined temporal coverage of observations from the 15 satellite instruments allowed considering the time period 1986–2014. In addition to the qualitative comparison of the time series, the agreement of the data sets is assessed quantitatively in the form of the spread (i.e. the difference between the maximum and minimum volume mixing ratio among the data sets), the (Pearson) correlation coefficient and the drift (i.e. linear changes of the difference between time series over time). Generally, good agreement between the time series was found in the middle stratosphere while larger differences were found in the lower mesosphere and near the tropopause. Concerning the latitude bands, the largest differences were found in the Antarctic while the best agreement was found for the tropics. From our assessment we find that all data sets can be considered in the future in observational and modelling studies addressing e.g. stratospheric and lower mesospheric water vapour variability and trends when data set specific characteristics (e.g. a drift) and restrictions (e.g. temporal and spatial coverage) are taken into account.

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