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"Amplitude variation with offset analysis."
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Elements of rock physics and their application to inversion and AVO studies
\"This book deals with a series of topics in rock physics, including elasticity, pore pressure, incompressibility of rocks and the Gassmann equation, fluid substitution, forward modeling and empirical equations, rock physics applications to AVO studies and inversion studies, and the Differential Effective Medium (DEM) method\"-- Provided by publisher.
Book
Amplitude-variation-with-offset, prestack waveform, and neural network inversion- A comparative study using real data example from the Rock Springs Uplift, Wyoming
In this work, I use seismic and well data to predict the subsurface geologic model. To accomplish this task, three approaches have been used: (1) amplitude-variation-with-offset inversion, (2) prestack waveform inversion, and (3) neural net inversion. Both amplitude-variation-with-offset and prestack waveform inversion are model-based inversions in which an initial (guess) model is iteratively modified until the synthetic (predicted) data from the model and underlying physics matches observation to reasonable accuracy. While the amplitude-variation-with-offset inversion uses a convolutional model for the underlying physics for computing synthetic data, the prestack waveform inversion uses a rigorous wave equation-based method to compute them. The neural network inversion, on the other hand, is a data-driven inversion methodology in which the network undergoes a series of training to derive linear/nonlinear relationships between the seismic attributes and the model attributes. Once such relations are established, they are used to predict the subsurface model directly from the seismic data. Using all three inversion methods on a single dataset from the Rock-springs uplift, Wyoming, it has been found that both amplitude-variation-with-offset and neural net inversions produce comparable results although the subsurface model estimated by the latter is of slightly higher resolution than the former. Prestack waveform inversion, even though compute-intense, is far superior to the other two inversion methods and should be the method of choice as the parallel computers with large number of compute-nodes become commonly available.
Dissertation
Global sinusoidal seasonality in precipitation isotopes
Quantifying seasonal variations in precipitation δ2H and δ18O is important for many stable isotope applications, including inferring plant water sources and streamflow ages. Our objective is to develop a data product that concisely quantifies the seasonality of stable isotope ratios in precipitation. We fit sine curves defined by amplitude, phase, and offset parameters to quantify annual precipitation isotope cycles at 653 meteorological stations on all seven continents. At most of these stations, including in tropical and subtropical regions, sine curves can represent the seasonal cycles in precipitation isotopes. Additionally, the amplitude, phase, and offset parameters of these sine curves correlate with site climatic and geographic characteristics. Multiple linear regression models based on these site characteristics capture most of the global variation in precipitation isotope amplitudes and offsets; while phase values were not well predicted by regression models globally, they were captured by zonal (0–30∘ and 30–90∘) regressions, which were then used to produce global maps. These global maps of sinusoidal seasonality in precipitation isotopes based on regression models were adjusted for the residual spatial variations that were not captured by the regression models. The resulting mean prediction errors were 0.49 ‰ for δ18O amplitude, 0.73 ‰ for δ18O offset (and 4.0 ‰ and 7.4 ‰ for δ2H amplitude and offset), 8 d for phase values at latitudes outside of 30∘, and 20 d for phase values at latitudes inside of 30∘. We make the gridded global maps of precipitation δ2H and δ18O seasonality publicly available. We also make tabulated site data and fitted sine curve parameters available to support the development of regionally calibrated models, which will often be more accurate than our global model for regionally specific studies.
Journal Article
Systematic Differences in Bucket Sea Surface Temperatures Caused by Misclassification of Engine Room Intake Measurements
Differences in sea surface temperature (SST) biases among groups of bucket measurements in the International Comprehensive Ocean–Atmosphere Dataset, version 3.0 (ICOADS3.0), were recently identified that introduce offsets of as much as 1°C and have first-order implications for regional temperature trends. In this study, the origin of these groupwise offsets is explored through covariation between offsets and diurnal cycle amplitudes. Examination of an extended bucket model leads to expectations for offsets and amplitudes to covary in either sign, whereas misclassified engine room intake (ERI) temperatures invariably lead to negative covariance on account of ERI measurements being warmer and having a smaller diurnal amplitude. An analysis of ICOADS3.0 SST measurements that are inferred to come from buckets indicates that offsets after the 1930s primarily result from the misclassification of ERI measurements in points of five lines of evidence. 1) Prior to when ERI measurements become available in the 1930s, offset–amplitude covariance is weak and generally positive, whereas covariance is stronger and generally negative subsequently. 2) The introduction of ERI measurements in the 1930s is accompanied by a wider range of offsets and diurnal amplitudes across groups, with 3) approximately 20% of estimated diurnal amplitudes being significantly smaller than buoy and drifter observations. 4) Regressions of offsets versus amplitudes intersect independently determined end-member values of ERI measurements. 5) Offset-amplitude slopes become less negative across all regions and seasons between 1960 and 1980, when ERI temperatures were independently determined to become less warmly biased. These results highlight the importance of accurately determining measurement procedures for bias corrections and reducing uncertainty in historical SST estimates.
Journal Article
Quantifying the effect of seasonal and vertical habitat tracking on planktonic foraminifera proxies
The composition of planktonic foraminiferal (PF) calcite is routinely used to reconstruct climate variability. However, PF ecology leaves a large imprint on the proxy signal: seasonal and vertical habitats of PF species vary spatially, causing variable offsets from annual mean surface conditions recorded by sedimentary assemblages. PF seasonality changes with temperature in a way that minimises the environmental change that individual species experience and it is not unlikely that changes in depth habitat also result from such habitat tracking. While this behaviour could lead to an underestimation of spatial or temporal trends as well as of variability in proxy records, most palaeoceanographic studies are (implicitly) based on the assumption of a constant habitat. Up to now, the effect of habitat tracking on foraminifera proxy records has not yet been formally quantified on a global scale. Here we attempt to characterise this effect on the amplitude of environmental change recorded in sedimentary PF using core top δ18O data from six species. We find that the offset from mean annual near-surface δ18O values varies with temperature, with PF δ18O indicating warmer than mean conditions in colder waters (on average by −0.1 ‰ (equivalent to 0.4 °C) per °C), thus providing a first-order quantification of the degree of underestimation due to habitat tracking. We use an empirical model to estimate the contribution of seasonality to the observed difference between PF and annual mean δ18O and use the residual Δδ18O to assess trends in calcification depth. Our analysis indicates that given an observation-based model parametrisation calcification depth increases with temperature in all species and sensitivity analysis suggests that a temperature-related seasonal habitat adjustment is essential to explain the observed isotope signal. Habitat tracking can thus lead to a significant reduction in the amplitude of recorded environmental change. However, we show that this behaviour is predictable. This allows accounting for habitat tracking, enabling more meaningful reconstructions and improved data–model comparison.
Journal Article
Near Surface Velocity Estimation Using GPR Data: Investigations by Numerical Simulation, and Experimental Approach with AVO Response
The velocity of near-surface materials is one of the most important for Ground-Penetrating Radar (GPR). In the study, we evaluate the options for determining the GPR velocity to measure the accuracy of velocity approximations from the acquired GPR data at an experimental site in Hangzhou, China. A vertical profile of interval velocities can be estimated from each common mid-point (CMP) gather using velocity spectrum analysis. Firstly, GPR data are acquired and analyzed using the popular method of hyperbola fitting which generated surprisingly high subsurface signal velocity estimates while, for the same profile, the Amplitude variation with offset (AVO) analysis of the GPR data (using the same hyperbola fitting method) generate a more reasonable subsurface signal velocity estimate. Several necessary processing steps are applied both for CMP and AVO analysis. Furthermore, experimental analysis is conducted on the same test site to get velocities of samples based on dielectric constant measurement during the drilling process. Synthetic velocities generated by AVO analysis are validated by the experimental velocities which confirmed the suitability of velocity interpretations.
Journal Article
Modified group theory-based optimization algorithms for numerical optimization
Group Theory-based Optimization Algorithm (GTOA) is a novel population-based global optimization algorithm, which is used to solve combinatorial optimization problems. This paper studies the applicability of GTOA in numerical optimization and proposes two versions of GTOA based on binary coding (GTOA-b) and 0∼9 integer coding (GTOA-d). Firstly, the coding transformation methods for representing the feasible solutions are introduced, which make GTOA suitable for continuous optimization. On this basis, the original evolution operators are modified to reduce the deviation and speed up global convergence. The experiment using the CEC2017 test suit is carried out to validate the performance of the algorithms. The influence of parameter values and the differences between the calculated results are analyzed by nonparametric tests. Computation results showed that the convergence rate of GTOA-d is faster than that of GTOA-b, and it achieved better results on the benchmark functions with higher dimensions. The comparison against twelve state-of-the-art and recently introduced meta-heuristic algorithms showed that GTOA-d has the superiority on convergence stability, it obtained significantly better performance than seven of its competitors. Finally, all the algorithms are applied to an Amplitude Variation with Offset inversion case study. The simulation showed that the proposed GTOA-d achieved satisfactory inversion results, and it has better performance in terms of convergence rate and average accuracy. The results demonstrate that the proposed GTOA-d is an effective algorithm for numerical optimization.
Journal Article
Symmetry between Theoretical and Physical Investigation of Water Contamination Using Amplitude Variation with Offset Analysis of Ground-Penetrating Radar Data
We evaluated the symmetry of theoretical and experimental analysis of water contamination such as non-aqueous phase liquid (NAPL) by using amplitude variations with offset analysis (AVO) of ground-penetrating radar (GPR) data. We used both theoretical and experimental approaches for AVO responses of GPR to small distributions of contamination. Theoretical modeling is a tool used to confirm the feasibility of geophysical surveys. Theoretical modeling of NAPL-contaminated sites containing wet sand—both with the water and light non-aqueous phase liquid—was applied by keeping in consideration the GPR AVO analysis in acquisition. Reflectivity was significantly altered with the changes in the contents of water and NAPL during modeling. The wet and dry sands introduced in our model changed two major phenomena: one, the wave pattern—implying a slight phase shift in the wave; and two, an amplitude jump with the dim reflection radar gram observed in the model. Experimental data were collected and analyzed; two observations were recorded during physical data analysis. First, relative permittivity confirmed the presence of NAPL in an experimental tank. Second, reflection patterns with jumps in amplitude and changes in polarity confirmed the theoretical investigation. Our results demonstrate that GPR AVO analysis can be as effective for detection of non-aqueous phase liquid (NAPLs) as it has been used to determine moisture contents in the past. The theoretical and experimental models were in symmetry, and both found a jump in reflection strength. The reflection pattern normally jumped with NAPL-intrusion. From the perspective of water contamination, this study emphasizes the need to take into account the impact of GPR AVO analyses along with the expert’s adaptive capacities.
Journal Article
A modified approach for Elastic Impedance Inversion due to the variation in value of K
Elastic impedance inversion is the latest development in the field of hydrocarbon exploration and production. The present research focuses on the improvement of the use of elastic impedance inversion, easing exploration of hydrocarbons. The seismic velocities change with variation in geological constraints. Constant K, which is S-wave to P-wave ratio of the nth layer and n+1 layer across the interface, it must be changed accordingly. This research focuses on testing the effects of K as a constant in the elastic impedance equation. As using the same value of K for all types of formations can give rise to severe errors in the interpretation of data. The importance of the value of K for particular Amplitude Variation with Offset AVO type (I-IV) is studied using different Elastic Impedance Equations. The Reflection Coefficient (RC) curves for each AVO class are generated using Zoeppritz approximation and Elastic Impedance equations. The comparison of RC curves shows significant variations at far offsets in each AVO type using the Constant value of K. When K Calculated is used, AVO type I and Type II shows a good match at near, mid and far offsets. Type III does not change due to the changing value of K. Type IV gives good agreement at near and intermediate offsets. This variation in curves, with the change in the value of K, indicates that it is a significant factor of interpretation using elastic impedance. The application of findings on well logs has given a satisfactory confirmation of the present results. This research can be helpful to resolve severe errors in the interpretation due to the constant value of K.
Journal Article
Joint inversion of PP and PS AVAZ data to estimate the fluid indicator in HTI medium: a case study in Western Sichuan Basin, China
The existence of fractures in an otherwise isotropic medium induces anisotropy in the medium. Because of existing in situ stress, most fractures are often aligned close to vertical, rendering a reservoir azimuthally anisotropic in character. Joint interpretation of PP and PS seismic data generally provides greater details in resolution of the estimated subsurface rock properties and geological structures than conventional PP seismic data. Here we report on the applicability of PP and PS azimuthal amplitude variation with offset (AVAZ) data in fracture characterization. The theory is based on a linear slip model and the Born formula such that PP- and PS-reflection coefficients are sensitive to fracture weaknesses. First we demonstrate numerical experiments with synthetic PP-AVAZ, PS-AVAZ and joint inversion to estimate fluid indicator. Results show that when the fractures have low saturation of gas, the fluid indicator estimated from PP-AVAZ data is fairly accurate. However, when gas saturation reaches up to 70%, joint inversion can help to improve the resulting poor quality in PP-AVAZ data inversion. For high values of gas-saturation, both PP inversion and joint inversion are sensitive to errors in background Poisson's ratio. Based on the result of our numerical experiment with synthetic data, we analyze a field dataset from the Western Sichuan Basin in China. The inversion result is consistent with well log based interpretation. All known reservoirs are accurately depicted by the estimated fluid indicator while the false gas zones interpreted by other methods are eliminated. When displayed as an inline section, the distribution of reservoirs appears consistent with the interpretation of the stratigraphy and geological structures.
Journal Article