Transient seepage analysis in zoned anisotropic soils based on the scaled boundary finite‐element method

The scaled boundary finite‐element method, a semi‐analytical computational scheme primarily developed for dynamic stiffness of unbounded domains, is applied to the analysis of unsteady seepage flow problems. This method is based on the finite‐element technology and gains the advantages of the boundary element method as well. Only boundary of the domain is discretized, no fundamental solution is required and singularity problems can be modeled rigorously. Anisotropic and non‐homogeneous materials satisfying similarity are modeled with no additional efforts. In this study, firstly, formulation of the method for the transient seepage flow problems is derived followed by its solution procedures. The accuracy, simplicity and applicability of the method are demonstrated via four numerical examples of transient seepage flow – three of them are available in the literature. Homogenous, non‐homogenous, isotropic and anisotropic material properties are considered to show the versatility of the technique. Excellent agreement with the finite‐element method is observed. The method out‐performs the finite‐element method in modeling singularity points. Copyright © 2014 John Wiley & Sons, Ltd.     

Laboratory and field investigations of rockburst phenomena using concurrent geotomographic imaging and acoustic emission/microseismic techniques

The progress made on three phases of a research project, started in 1986 to investigate mining induced seismicity/rockburst phenomena using concurrent geotomographic imaging and microseismic monitoring techniques, is described. Phase I is the geotomographic software development and laboratory calibration trials. Phase II is the enhancement of traditional microseismic monitoring instrumentation with a waveform acquisition system, so that source mechanism studies can be carried out on mining induced seismic events. Phase III is the field trials of the hybrid technique which will be used to monitor changing rock mass physical properties, in response to mining. Preliminary results from all three phases are given, together with an outline of current and future research planned.Presented at the Fred Leighton Memorial Workshop on Mining Induced Seismicity, Montreal 1987.     

A Seismic Model of Casing Failure in Oil Fields

—We develop a seismic model that characterises the sudden tensional failure of oil-well casings. The energy released by the rupture of a well casing is transformed into heat and seismic energy. The upper bound of the seismic efficiency of this process is estimated at about 3%. The static situation at the completion of a casing failure episode is modelled by calculating the static displacement field generated by two opposing forces separated by an arm. The azimuthal patterns of these displacements and the change in the strain and stress fields caused by the force couple are described. The dynamics of the failure episode are modelled as a dipole with a seismic moment equivalent to the product of the average drop in shear stress, the failure surface, and an arm. The radiated P and S waves have mean-square radiation pattern coefficients of 1/5 for P waves and 2/15 for S waves. The displacement field as a function of time during rupture and the spectral properties in the far field are derived. The most promising seismic parameters that can be used for distinguishing between casing failure events and other possible events are polarisation properties of S waves and S/P amplitude ratios. S-wave polarisation distinguishes between shear events and casing failure events. S/P amplitude ratios distin guish between tensile events and casing failure events.     

Surficial and Deep Earth Material Prediction from Geochemical Compositions

Prediction of true classes of surficial and deep earth materials using multivariate spatial data is a common challenge for geoscience modelers. Most geological processes leave a footprint that can be explored by geochemical data analysis. These footprints are normally complex statistical and spatial patterns buried deep in the high-dimensional compositional space. This paper proposes a spatial predictive model for classification of surficial and deep earth materials derived from the geochemical composition of surface regolith. The model is based on a combination of geostatistical simulation and machine learning approaches. A random forest predictive model is trained, and features are ranked based on their contribution to the predictive model. To generate potential and uncertainty maps, compositional data are simulated at unsampled locations via a chain of transformations (isometric log-ratio transformation followed by the flow anamorphosis) and geostatistical simulation. The simulated results are subsequently back-transformed to the original compositional space. The trained predictive model is used to estimate the probability of classes for simulated compositions. The proposed approach is illustrated through two case studies. In the first case study, the major crustal blocks of the Australian continent are predicted from the surface regolith geochemistry of the National Geochemical Survey of Australia project. The aim of the second case study is to discover the superficial deposits (peat) from the regional-scale soil geochemical data of the Tellus Project. The accuracy of the results in these two case studies confirms the usefulness of the proposed method for geological class prediction and geological process discovery.

     

A Truly Spatial Random Forests Algorithm for Geoscience Data Analysis and Modelling

Mathematical Geosciences - Spatial data mining helps to find hidden but potentially informative patterns from large and high-dimensional geoscience data. Non-spatial learners generally look at the...     

Seismicity and Casing Failures Due to Steam Stimulation in Oil Sands

—This paper describes observations of seismicity and casing failures associated with steam stimulation operations at Imperial Oil Ltd.’s Cold Lake oil field in Alberta, Canada. A total of 11 oil-producing pads were monitored over a 1–2 year period using 3-component geophones cemented at depths ranging from 160 m to 400 m and data acquisition systems with a flat frequency response up to 1.5 kHz. Most of the seismicity was detected during the steaming operations and was located in the formation overlying the oil-bearing layer. Some activity was observed in the shales above, however, the reservoir itself showed almost no evidence of seismicity. The estimated seismic moment of the observed events was in the range 10⁵–10⁷ N·m (?2.7 < M < ?1.3). According to a theoretical model (Talebi et al., 1998) and in situ observations, the seismic source corresponding to casing failure events should be well described by a dipole registering seismic moment in the order of 2 · 10⁶ N·m. Seismic signals of a total of four observed casing failures were analyzed. The partial failures produced seismic moments slightly lower than this value while total failures were stronger by about one order of magnitude. The use of the SV/SH amplitude ratio, in conjunction with accurate source locations, provided a robust technique for the detection of casing failures.     

Injection-induced Microseismicity in Colorado Shales

—Imperial Oil Resources Limited uses cyclic steam stimulation to recover oil from their Cold Lake oil field in Alberta. This operation, in particular situations, can be associated with the failure of well casings in the Colorado shales above the oil-bearing formation. A number of fluid injection operations was undertaken at this site and the associated microseismicity was detected using two three-component geophones and fifteen hydrophones. The purpose of this experiment was to simulate the occurrence of a casing failure, determine the feasibility of monitoring in a shallow environment, and characterize the microseismic activity. A calibration survey provided values of 1786 ± 108 m/s for P-wave velocity, 643 ± 56 m/s for S-wave velocity and 0.428 ± 0.017 for Poisson’s ratio in the shale formation. Estimates of the quality factor Q _P were 15 for the horizontal direction and 38 for the vertical direction, corroborating the evidence of velocity anisotropy. Calibration shots were located to within 10 m of the actual shot points using triangulation and polarization techniques. Several hundred microseis mic events were recorded and 135 events were located. The results showed that microseismic activity was confined to depths within 10 meters of the injection depth. The experiment clearly established the feasibility of detecting microseismicity induced by fluid injection rates typical of casing failures in shales at distances over 100 m.     

A reappraisal of active faults in central-east Iran (Kerman province)

Fault lineaments are the main input data in earthquake engineering and seismology studies. This study presents a digitally-based active fault map of the Kerman region in central-east Iran which experienced several devastating earthquakes on poorly exposed and/or not identified active faults. Using Landsat 8 data, we have carried out the image-based procedures of fault mapping, which include applying the contrast stretching technique, the principal component analysis, the color composite technique, the spectral rationing, and creating the false-color composite images. Besides, we have cross-checked the resulting map with the geological maps provided by the Geological Survey of Iran to decrease the associated uncertainties. The resulting map includes 123 fault segments, still, a part of which has been expressed in the previously compiled active-fault maps of Iran. Indeed, the new one is mapping the poorly exposed active faults, so-called secondary faults, which are able to produce strong events. These faults are primarily associated with poorly defined areas that accommodate low levels of seismicity; however, sporadic strong events are likely to occur. It has also been investigated that these kinds of faults are seismogenic and are able to produce destructive events. In total, the outcome of this study can also be jointed with seismic studies for investigating parts of the earthquake activity in central-east Iran, in particular for the fault-based approaches in impending earthquake-resistant buildings.     

Fast bioremediation of petroleum-contaminated soils by a consortium of biosurfactant/bioemulsifier producing bacteria

Biodegradation of petroleum hydrocarbons as a decontamination mechanism is a relatively slow process. This study aimed to investigate the impact of a tailored consortium of bacteria with higher capacities in biosurfactant production and biodegradation on the acceleration of the biodecontamination process. To this end, 18 biosurfactant producing bacteria were isolated from the crude oil-contaminated soil samples of Isfahan refinery, and the activity of the produced biosurfactants was measured in terms of surface tension reduction and emulsification E24 test. Then, the isolates screened for the biodegradation of kerosene hydrocarbons and chemical structure of the purified biosurfactants produced by the most efficient isolates were partially characterized. Next, the isolates were sorted based on their surfactant activity and biodegradation efficiency, and the higher ranked bacteria thus selected were utilized to form an efficient consortium removing hydrocarbons from the oil-contaminated soil samples in a slurry phase system. The consortium consisted of Bacillus subtilis tb1 and Pseudomonas aeruginosa species having the highest biodegradation capabilities and surface activities. The results revealed that the hydrocarbon removal efficiency of the consortium was at least 25 % higher than single species, and the final removal efficiency for the consortium could be reached in a considerably shorter time.