John E. Peterson

Applications of algebraic reconstruction techniques to crosshole seismic data

Tomographic imaging techniques were applied to two crosshole data sets to determine the velocity structures and the reliability and resolution of the algorithms on real data. The experiments were carried out at the Retsoff salt mine in New York and at the underground radioactive waste study site at the Stripa mine facility in Sweden. The traveltimes at Restoff were high quality and were obtained over raypaths of up to 500 m in length. The structure was quite complicated with velocity contrasts up to 50 percent. The Stripa site was in granitic rock with velocity contrasts of only a few percent. The dimensions of the experiment were small with maximum ray lengths of just over 10 m. The data at this site were collected with very high accuracy, source and receiver locations were measured to better than 1.0 mm, and traveltimes were read to 0.001 ms. A number of algorithms similar to the algebraic reconstruction techniques (ART) used in medical imaging have been applied to the data. Some modifications of the algorithms, such as the application of weighting schemes, damping parameters, and curved raypaths, were performed. The resulting velocity fields were compared to the known fields and with each other to determine an optimal method. The algorithms were found to be a rapid, reliable means of reconstructing the slowness field of real data. Low-velocity zones were recovered with accuracy in location and value. It was also found that great care was necessary in application of the techniques to ensure that proper damping parameters are used and the proper number of iterations taken; otherwise poor reconstructions will result.

Hydrogeological characterization of the south oyster bacterial transport site using geophysical data

A multidisciplinary research team has conducted a field-scale bacterial transport study within an uncontaminated sandy Pleistocene aquifer near Oyster, Virginia. The overall goal of the project was to evaluate the importance of heterogeneities in controlling the field-scale transport of bacteria that are injected into the ground for remediation purposes. Geochemical, hydrological, geological, and geophysical data were collected to characterize the site prior to conducting chemical and bacterial injection experiments. In this paper we focus on results of a hydrogeological characterization effort using geophysical data collected across a range of spatial scales. The geophysical data employed include surface ground-penetrating radar, radar cross-hole tomography, seismic cross-hole tomography, cone penetrometer, and borehole electromagnetic flowmeter. These data were used to interpret the subregional and local stratigraphy, to provide high-resolution hydraulic conductivity estimates, and to provide information about the log conductivity spatial correlation function. The information from geophysical data was used to guide and assist the field operations and to constrain the numerical bacterial transport model. Although more field work of this nature is necessary to validate the usefulness and cost-effectiveness of including geophysical data in the characterization effort, qualitative and quantitative comparisons between tomographically obtained flow and transport parameter estimates with hydraulic well bore and bromide breakthrough measurements suggest that geophysical data can provide valuable, high-resolution information. This information, traditionally only partially obtainable by performing extensive and intrusive well bore sampling, may help to reduce the ambiguity associated with hydrogeological heterogeneity that is often encountered when interpreting field-scale bacterial transport data.

Quantifying and relating land-surface and subsurface variability in permafrost environments using LiDAR and surface geophysical datasets

The value of remote sensing and surface geophysical data for characterizing the spatial variability and relationships between land-surface and subsurface properties was explored in an Alaska (USA) coastal plain ecosystem. At this site, a nested suite of measurements was collected within a region where the land surface was dominated by polygons, including: LiDAR data; ground-penetrating radar, electromagnetic, and electrical-resistance tomography data; active-layer depth, soil temperature, soil-moisture content, soil texture, soil carbon and nitrogen content; and pore-fluid cations. LiDAR data were used to extract geomorphic metrics, which potentially indicate drainage potential. Geophysical data were used to characterize active-layer depth, soil-moisture content, and permafrost variability. Cluster analysis of the LiDAR and geophysical attributes revealed the presence of three spatial zones, which had unique distributions of geomorphic, hydrological, thermal, and geochemical properties. The correspondence between the LiDAR-based geomorphic zonation and the geophysics-based active-layer and permafrost zonation highlights the significant linkage between these ecosystem compartments. This study suggests the potential of combining LiDAR and surface geophysical measurements for providing high-resolution information about land-surface and subsurface properties as well as their spatial variations and linkages, all of which are important for quantifying terrestrial-ecosystem evolution and feedbacks to climate.ResuméLa portée de la télédétection et des données géophysique de surface pour caractériser la variabilité spatiale et les relations entre la surface du terrain et les propriétés de la subsurface a été étudiée sous tous ses aspects dans l’écosystème de la plaine côtière d’Alaska (USA). Dans cette région, sur un site où la surface du sol est dominée par des polygones, une série de données se recoupant a été collectée, incluant : données LiDAR; géoradar, tomographie électromagnétique et résistivité; profondeur de la couche aquifère, température, teneur en humidité, texture, teneur en carbone et en azote du sol; et cations du fluide des pores. Les données Lidar ont été utilisées pour établir les cotes géomorphiques, qui peuvent indiquer un drainage potentiel. Des données géophysiques ont été utilisées pour déterminer la profondeur de la couche aquifère, la teneur en humidité du sol, et la variabilité du pergélisol. L’analyse par agglomérat des données LiDAR et des attributs géophysiques ont révélé la présence de trois zones spatiales ayant une distribution similaire des propriétés géomorphiques, hydrogéologiques, thermales et géochimiques. La correspondance entre la zonation géomorphique basée sur LiDAR, la couche aquifère selon la géophysique et la zonation permafrost, met en lumière la relation significative entre ces compartiments de l’écosystème. Cette étude montre le potentiel d’une combinaison des mesures LiDAR et des mesures géophysiques de surface pour fournir une information haute résolution sur les propriétés de surface et de subsurface du sol aussi bien que sur leur variations spatiales et liens, toutes étant importantes pour quantifier l’évolution de l’écosystème terrestre et les réponses au climat.ResumenSe exploró el valor de los sensores remotos y de los datos geofísicos de superficie para caracterizar la variabilidad espacial y las relaciones entre la superficie y las propiedades subsuperficiales en un ecosistema de planicie costera en Alaska (EEUU). En este sitio, un conjunto anidado de medidas fue colectado dentro de una región donde la superficie estaba dominada por polígonos, incluyendo: datos LiDAR; datos de radar, electromagnéticos, y tomografías de resistividad eléctrica; profundidad de la capa activa, temperatura del suelo, contenido de humedad del suelo, textura del suelo, contenido de carbono y nitrógeno en suelo; y cationes del fluido de poros. Los datos LiDAR fueron usados para extraer los indicadores geomórficos, que posiblemente indican un drenaje potencial. Los datos geofísicos fueron para caracterizar la profundidad de la capa activa, el contenido de humedad del suelo y la variabilidad del permafrost. En análisis de cluster de los LiDAR y los atributos geofísicos revelaron la presencia espacial de tres zonas, que tenían una única distribución de propiedades geomórficas, hidrológicas, térmicas y geoquímicas. La correspondencia entre la zonación geomórfica basada en LiDAR y la capa activa basada en geofísica y la zonación del permafrost destaca la vinculación significativa entre estos compartimentos del ecosistema. Este estudio sugiere el potencial de la combinación LiDAR y las mediciones geofísicas de superficie para proveer información de alta resolución acerca de las propiedades de la superficie y de la subsuperficie así como su variación espacial y su articulación, todos los cuales son importantes para cuantificar la evolución del ecosistema terrestre y las reacciones con el clima.摘要用来描述地表和地下性质的空间变异性和两者之间的关系的遥感和地面地球物理数据已在阿拉斯加(美国)的一个沿海平原生态系统进行了探讨。在本次研究场地的一个表面呈多边形的区域收集到了一套测量数据,包括激光雷达数据;探地雷达数据,电磁和电阻断层扫描数据;活性层深度,土壤温度,土壤水气含量,土壤质地,土壤碳和氮的含量;以及孔隙流体阳离子数据。激光雷达数据用来提取地貌指标,这可能指示出潜在的排泄。地球物理数据用来刻画活性层的深度,土壤水气含量和永久冻土的变化特征。通过对激光雷达和地球物理数据属性的聚类分析发现了三个在地形,水文,热和地球化学性质分布上存在异常的空间区域。基于激光雷达测量的地貌分区与基于地球物理数据的活性层和永久冻土分区之间的对应关系突出了这些生态系统分区间的紧密联系。本次研究表明可以通过结合激光雷达和地表地球物理测量来为地表和地下的性质以及它们在空间上的变化和关系提供高分辨率的信息,所有这些对于量化陆地生态系统的演化和对气候变化的反应都是非常重要的。ResumoNum ecossistema da planície costeira do Alaska (EUA) foi explorado o valor da deteção remota e de dados de geofísica de superfície para caracterizar a variabilidade espacial e as relações entre propriedades da superfície do terreno e da subsuperfície. Neste local, inserido numa região onde o terreno superficial é dominado por polígonos, foi recolhido um conjunto agregado de medições, incluindo: dados de LiDAR; dados de geoadar, eletromagnéticos e de tomografia de resistência elétrica; profundidade da camada ativa, temperatura do solo, teor de água no solo, textura do solo, teor de carbono e azoto no solo; e catiões no fluido poroso. Os dados LiDAR foram usados para extrair dimensões geomórficas que potencialmente indicam o potencial de drenagem. Os dados geofísicos foram usados para caracterizar a profundidade da camada ativa, o teor de humidade no solo e a variabilidade no permafrost. A análise grupal de atributos LiDAR e geofísicos revelou a presença de três zonas espaciais que tinham distribuições únicas de propriedades geomórficas, hidrológicas, térmicas e geoquímicas. A correspondência entre o zonamento geomórfico baseado no LiDAR e a zonação da camada activa baseada na geofísica e do permafrost, demonstra a significativa conexão entre estes compartimentos do ecossistema. Este estudo sugere o potencial da combinação de medições de LiDAR e de geofísica de superfície para fornecer informação de alta resolução acerca das propriedades da superfície do terreno e da subsuperfície, assim como sobre as variações espaciais e conexões, sendo todas elas importantes para a quantificação da evolução do ecossistema terrestre e as retroações com o clima.

Joint inversion of crosshole radar and seismic traveltimes acquired at the South Oyster Bacterial Transport Site

The structural approach to joint inversion, entailing common boundaries or gradients, offers a flexible and effective way to invert diverse types of surface-based and/or crosshole geophysical data. The cross-gradients function has been introduced as a means to construct models in which spatial changes in two distinct physical-property models are parallel or antiparallel. Inversion methods that use such structural constraints also provide estimates of nonlinear and nonunique field-scale relationships between model parameters. Here, we jointly invert crosshole radar and seismic traveltimes for structurally similar models using an iterative nonlinear traveltime tomography algorithm. Application of the inversion scheme to synthetic data demonstrates that it better resolves lithologic boundaries than the individual inversions alone. Tests of the scheme on GPR and seismic data acquired within a shallow aquifer illustrate that the resultant models have improved correlations with flowmeter data in comparison with models based on individual inversions. The highest correlation with the flowmeter data is obtained when the joint inversion is combined with a stochastic regularization operator and the vertical integral scale is estimated from the flowmeter data. Point-spread functions show that the most significant resolution improvements offered by the joint inversion are in the horizontal direction.

Development of a joint hydrogeophysical inversion approach and application to a contaminated fractured aquifer

This paper presents a joint inversion approach for combining crosshole seismic travel time and borehole flowmeter test data to estimate hydrogeological zonation. The approach is applied to a complex, fractured Department of Energy field site located at the Oak Ridge National Laboratory in Tennessee, United States. We consider seismic slowness (the inverse of seismic velocity) and hydrogeological zonation indicators as unknown variables and use a physically based model with unknown parameters to relate the seismic slowness to the zonation indicators. We jointly estimate all the unknown parameters in the model by conditioning them to the crosshole seismic travel times as well as the borehole flowmeter data using a Bayesian model and a Markov chain Monte Carlo sampling method. The fracture zonation estimates are qualitatively compared to bromide tracer breakthrough data and to uranium biostimulation experiment results. The comparison suggests that the joint inversion approach adequately estimated the fractured zonation and that the fracture zonation influenced biostimulation efficacy. Our study suggests that the new joint hydrogeophysical inversion approach is flexible and effective for integrating various types of data sets within complex subsurface environments and that seismic travel time data have the potential to provide valuable information about fracture zonation.

Fracture detection using crosswell and single well surveys

We recorded high‐resolution (1 to 10 kHz), crosswell and single well seismic data in a shallow (15 to 35 m), water‐saturated, fractured limestone sequence at Conocos borehole test facility near Newkirk, Oklahoma. Our objective was to develop seismic methodologies for imaging gas‐filled fractures in naturally fractured gas reservoirs. The crosswell (1/4 m receiver spacing, 50 to 100 m well separation) surveys used a piezoelectric source and hydrophones before, during, and after an air injection that we designed to displace water from a fracture zone. Our intent was to increase the visibility of the fracture zone to seismic imaging and to confirm previous hydrologic data that indicated a preferred pathway. For the single well seismic imaging (a piezoelectric source and an eight‐element hydrophone array at 1/4 m spacing), we also recorded data before and after the air injection. The crosswell results indicate that the air did follow a preferred pathway that was predicted by hydrologic modeling. In addition,...

Extrapolating active layer thickness measurements across Arctic polygonal terrain using LiDAR and NDVI data sets.

Landscape attributes that vary with microtopography, such as active layer thickness (ALT), are labor intensive and difficult to document effectively through in situ methods at kilometer spatial extents, thus rendering remotely sensed methods desirable. Spatially explicit estimates of ALT can provide critically needed data for parameterization, initialization, and evaluation of Arctic terrestrial models. In this work, we demonstrate a new approach using high-resolution remotely sensed data for estimating centimeter-scale ALT in a 5 km2 area of ice-wedge polygon terrain in Barrow, Alaska. We use a simple regression-based, machine learning data-fusion algorithm that uses topographic and spectral metrics derived from multisensor data (LiDAR and WorldView-2) to estimate ALT (2 m spatial resolution) across the study area. Comparison of the ALT estimates with ground-based measurements, indicates the accuracy (r2 = 0.76, RMSE ±4.4 cm) of the approach. While it is generally accepted that broad climatic variability associated with increasing air temperature will govern the regional averages of ALT, consistent with prior studies, our findings using high-resolution LiDAR and WorldView-2 data, show that smaller-scale variability in ALT is controlled by local eco-hydro-geomorphic factors. This work demonstrates a path forward for mapping ALT at high spatial resolution and across sufficiently large regions for improved understanding and predictions of coupled dynamics among permafrost, hydrology, and land-surface processes from readily available remote sensing data.

Monitoring CO2 Intrusion and Associated Geochemical Transformations in a Shallow Groundwater System Using Complex Electrical Methods

The risk of CO(2) leakage from a properly permitted deep geologic storage facility is expected to be very low. However, if leakage occurs it could potentially impact potable groundwater quality. Dissolved CO(2) in groundwater decreases pH, which can mobilize naturally occurring trace metals commonly contained in aquifer sediments. Observing such processes requires adequate monitoring strategies. Here, we use laboratory and field experiments to explore the sensitivity of time-lapse complex resistivity responses for remotely monitoring dissolved CO(2) distribution and geochemical transformations that may impact groundwater quality. Results show that electrical resistivity and phase responses correlate well with dissolved CO(2) injection processes. Specifically, resistivity initially decreases due to increase of bicarbonate and dissolved species. As pH continues to decrease, the resistivity rebounds toward initial conditions due to the transition of bicarbonate into nondissociated carbonic acid, which reduces the total concentration of dissociated species and thus the water conductivity. An electrical phase decrease is also observed, which is interpreted to be driven by the decrease of surface charge density as well as potential mineral dissolution and ion exchange. Both laboratory and field experiments demonstrate the potential of field complex resistivity method for remotely monitoring changes in groundwater quality due to CO(2) leakage.

EXPERIMENTAL DETECTION OF REINFORCING BAR CORROSION USING NONDESTRUCTIVE GEOPHYSICAL TECHNIQUES

This research used electrical impedance and ground penetrating radar (GPR) methods to indicate corrosion of steel reinforcing bars embedded in a concrete block. Corrosion of the reinforcing bars was accelerated using an anodic polarization technique. Measurements were collected using both geophysical techniques before and after the corrosion experiments. Analysis of the geophysical measurements indicated the potential benefits and limitations of the 2 geophysical methods for assessing corrosion of reinforcing bars. GPR methods have the advantage of providing a quick indication of alterations at the interface of the rebar surface and the surrounding concrete, and they have the potential to yield very high spatial resolution data. Indications that corrosion had occurred were independently and consistently obtained from the 2 geophysical methods, and observations were also corroborated by visual examination of the rebar corrosion state by destructive analysis of the experimental block.

Nonuniqueness in traveltime tomography: Ensemble inference and cluster analysis

We examine the nonlinear aspects of seismic traveltime tomography. This is accomplished by completing an extensive set of conjugate gradient inversions on a parallel virtual machine, with each initiated by a different starting model. The goal is an exploratory analysis of a set of conjugate gradient solutions to the traveltime tomography problem. We find that distinct local minima are generated when prior constraints are imposed on traveltime tomographic inverse problems. Methods from cluster analysis determine the number and location of the isolated solutions to the traveltime tomography problem. We apply the cluster analysis techniques to a cross-borehole traveltime data set gathered at the Gypsy Pilot Site in Pawnee County, Oklahoma. We find that the 1075 final models, satisfying the traveltime data and a model norm penalty, form up to 61 separate solutions. All solutions appear to contain a central low velocity zone bounded above and below by higher velocity layers. Such a structure agrees with well-logs, hydrological well tests, and a previous seismic inversion.