Dissertations / Theses on the topic 'Geophysics Geophysics'

The first part of my thesis is mainly focused on the effect of grain size distribution on compaction localization in porous sandstone. To identify the microstructural parameters that influence compaction band formation, I conducted a systematic study of mechanical deformation, failure mode and microstructural evolution in Bleurswiller and Boise sandstones, of similar porosity (∼25%) and mineralogy but different sorting. Discrete compaction bands were observed to develop over a wide range of pressure in the Bleurswiller sandstone that has a relatively uniform grain size distribution. In contrast, compaction localization was not observed in the poorly sorted Boise sandstone. My results demonstrate that grain size distribution exerts important influence on compaction band development, in agreement with recently published data from Valley of Fire and Buckskin Gulch, as well as numerical studies.

The second part aimed to improve current knowledge on inelastic behavior, failure mode and brittle-ductile transition in another sedimentary rock, porous carbonates. A micritic Tavel (porosity of ∼13%) and an allochemical Indiana (∼18%) limestones were deformed under compaction in wet and dry conditions. At lower confining pressures, shear localization occurred in brittle faulting regime. Through transitional regime, the deformation switched to cataclastic flow regime at higher confining pressure. Specifically in the cataclastic regime, the (dry and wet) Tavel and dry Indiana failed by distributed cataclastic flow, while in contrast, wet Indiana failed as compaction localization. My results demonstrate that different failure modes and mechanical behaviors under different deformation regimes and water saturation are fundamental prior to any geophysical application in porous carbonates.

The third part aimed to focus on investigating compaction on quartz aggregate starting at low (MPa) using X-ray diffraction. We report the diffraction peak evolution of quartz with increasing pressures. Through evaluating the unit cell lattice parameters and the volume of the quartz sample, macroscopic stress and strain were resolved. Moreover, we observed quartz peak broadened asymmetrically at low pressure, such extent is more prominent in axial than in radial direction. Our evaluation on peak [101] (highest intensity among peaks) demonstrated that full width at half maximum can be a good proxy for microscopic stress distribution. We observed deviations in the pressure-volume curves at P = ∼0.4 GPa and speculated that it was the point of which onset of grain crushing and pore collapse occur in quartz. This is on the same order of which onset of grain crushing (commonly known as P*) is observed in sandstones in the rock mechanics literature. This demonstrated that there is potential in estimating grain crushing and pore collapse pressure with our technique.

Brittleness is a key characteristic for effective reservoir stimulation and is mainly controlled by mineralogy in unconventional reservoirs. Unfortunately, there is no universally accepted means of predicting brittleness from measures made in wells or from surface seismic data. Brittleness indices (BI) are based on mineralogy, while brittleness average estimations are based on Young's modulus and Poisson's ratio. I evaluate two of the more popular brittleness estimation techniques and apply them to a Barnett Shale seismic survey in order to estimate its geomechanical properties. Using specialized logging tools such as elemental capture tool, density, and P- and S wave sonic logs calibrated to previous core descriptions and laboratory measurements, I create a survey-specific BI template in Young's modulus versus Poisson's ratio or alternatively λρ versus μρ space. I use this template to predict BI from elastic parameters computed from surface seismic data, providing a continuous estimate of BI estimate in the Barnett Shale survey. Extracting λρ-μρ values from microseismic event locations, I compute brittleness index from the template and find that most microsemic events occur in the more brittle part of the reservoir. My template is validated through a suite of microseismic experiments that shows most events occurring in brittle zones, fewer events in the ductile shale, and fewer events still in the limestone fracture barriers.

Estimated ultimate recovery (EUR) is an estimate of the expected total production of oil and/or gas for the economic life of a well and is widely used in the evaluation of resource play reserves. In the literature it is possible to find several approaches for forecasting purposes and economic analyses. However, the extension to newer infill wells is somewhat challenging because production forecasts in unconventional reservoirs are a function of both completion effectiveness and reservoir quality. For shale gas reservoirs, completion effectiveness is a function not only of the length of the horizontal wells, but also of the number and size of the hydraulic fracture treatments in a multistage completion. These considerations also include the volume of proppant placed, proppant concentration, total perforation length, and number of clusters, while reservoir quality is dependent on properties such as the spatial variations in permeability, porosity, stress, and mechanical properties. I evaluate parametric methods such as multi-linear regression, and compare it to a non-parameteric ACE to better correlate production to engineering attributes for two datasets in the Haynesville Shale play and the Barnett Shale. I find that the parametric methods are useful for an exploratory analysis of the relationship among several variables and are useful to guide the selection of a more sophisticated parametric functional form, when the underlying functional relationship is unknown. Non-parametric regression, on the other hand, is entirely data-driven and does not rely on a pre-specified functional forms. The transformations generated by the ACE algorithm facilitate the identification of appropriate, and possibly meaningful, functional forms.

Reservoir properties are mainly determined based on well log information. However, wells in most reservoirs are sparse and widely spread compared to the size of the reservoir. Seismic data is thus one of the most important complementary sources of information used to build 3D models of hydrocarbon reservoirs. The need for a high quality reservoir description starts as soon as a discovery is made. In the appraisal phase, hydrocarbons in place and the amount of recoverable reserves are estimated based on the reservoir model. Improved structural models are also needed in optimal well placement during the production and development phase of a reservoir. Knowledge about saturation and pressure distributions in a reservoir are valuable both in the exploration and development phase of a reservoir. This knowledge is used to evaluate the size of a field, determine an optimal drainage pattern, and decide on optimal well design to reduce risks for blow-outs and damage on production equipment. Reducing uncertainty in reservoir property estimates from seismic data have large economic impact on the development of a hydrocarbon reservoir.

Quantitative reservoir property information can be obtained either through direct estimates of reservoir properties from seismic data or through estimates of elastic properties (velocities and densities) that are related to reservoir properties. The relationship between physical properties of rocks and fluids and P-wave seismic data are often empirical and non-unique. This leads to large uncertainties in reservoir models derived from pressure wave seismic data alone. Since shear waves do not propagate through fluids, combined use of pressure wave seismic data and shear wave seismic data might increase our ability to derive fluid and lithology properties from seismic data. One way to obtain information about shear wave velocities over a large area is to acquire multicomponent seismic data (for instance x, y, and z component geophone data). Parts of this thesis focus on methods to combine the information from multicomponent seismic data with pressure wave (hydrophone) seismic data. In this way we improve the accuracy in the estimates of pressure wave velocity, shear wave velocity and density in the subsurface.

To obtain information about changes in reservoir parameters like fluid saturation and pore pressure during production, comparisons between different vintages of seismic data acquired over the field can be performed. Differences in the seismic signal from the same area over a time period (time-lapse seismic data) can be interpreted as changes in reservoir properties. Benefits of improved reservoir characterization include ability to locate bypassed oil and mapping of fluid fronts. This leads to saved costs due to reduced number of misplaced wells, and increased production because of optimized well placement. In the early days of seismic reservoir monitoring, the analyses were qualitative, e.g. to identify undrained areas, analyzing the sealing capacity of faults, and detect drainage patterns. Today, time-lapse seismic analysis is still mainly qualitative. To be able to obtain more quantitative estimates of changes in reservoir properties from the time-lapse seismic data, we need to establish links between the rock parameters and the seismic data. I have used both time-lapse surface seismic data and time-lapse multicomponent seismic data to estimate production related changes in fluid saturation and pressure.

Finally, to be able to utilize rock physical information obtained from seismic reservoir characterization in reservoir modelling, information about uncertainties in the estimates are essential. One way to do this is to use deterministic models (rock physics models) that relates reservoir properties to seismic data, and assume that the model parameters are independent. However, the variables in these estimations are inherently dependent and should be treated as such. By formulating the problem in a Bayesian framework, dependencies between the different variables and spatial dependencies can easily be included. I have used both deterministic uncertainty analysis and Bayesian estimation methods to quantify uncertainties in the estimates.

Thermophysical properties (dissociation enthalpy, heat capacity, metastability) and compositional properties (hydrate number, free water and fractionation) of natural gas hydrate were studied experimentally on samples that contained large amounts of ice. Methods for continuous hydrate production and sampling, and for quantification of the properties were developed. Hydrate was produced from a natural gas of ethane (5 %mol) and propane (3 %mol) in methane.

A low temperature scanning calorimetry method was developed to measure dissociation enthalpy, heat capacity, hydrate number and free water (ice). During the analysis, the hydrate samples were pressurized to 1.7 MPa with methane and the system operated between the hydrate equilibrium curves of methane and the hydrate forming natural gas. A sample conditioning procedure eliminated thermal effects of desorption as the ice melted. Desorption occurred since the samples were produced and refrigerated to 255 K under a natural gas pressure of 6-10 MPa, but were analyzed and melted under a methane pressure of 1.7 MPa.

A low temperature isothermal calorimetry method was developed to quantify the metastability properties. Metastability was confirmed for temperatures up to 268 K and quantified in terms of the low dissociation rate.

Fractionation data were obtained in the range 3.0 to 7.5 MPa and for subcoolings between 2 and 16 K. High pressure and large subcooling is desirable to suppress fractionation. A fractionation model was proposed. The model coincides with the van der Waals-Platteeuw model for zero subcooling. No fractionation is assumed for hypothetical hydrate formation at infinite driving force (subcooling). Between these two extremes an exponential term was used to describe the fractionation. The model predicted fractionation with an accuracy of about 1%abs corresponding to 1-10%rel.

Estimating an accurate velocity model is crucial for seismic imaging to obtain a good understanding of the subsurface structure. The objective of this thesis is to investigate methods of velocity analysis by optimizing seismic images.

A conventional seismic image is obtained by zero-lag crosscorrelation of wavefields extrapolated from a source wavelet and recorded data on the surface using a velocity model. The velocity model provides the kinematic information needed by the imaging algorithm to position the reflectors at correct locations and to focus the image. In complex geology, wave-equation migration is a powerful tool for accurately imaging the earth's interior; the quality of the output image, however, depends on the accuracy of the velocity model. Given such a dependency between the image and model, analyzing the velocity information from the image is still not intuitive and often ambiguous. If the nonzero space- and time-lags information are preserved in the crosscorrelation, the output are image hypercube defined as extended images. Compared to the conventional image, the extended images provide a straightforward way to analyze the image quality and to characterize the velocity model accuracy.

Understanding the reflection moveout is the key to developing velocity model building methods using extended images. In the extended image space, reflections form coherent objects which depend on space (lags) and time (lags). These objects resemble cones which ideally have their apex at zero space and time lags. The symmetry axis of the cone lies along the time-lag axis. The apex of the cone is located at zero lags only if the velocity model is accurate. This corresponds to the situation when reflection energy focuses at origin in both the space- and time-lag common-image gathers (the slices at zero time and space lags, respectively). When the velocity model is inaccurate, the cone shifts along the time-lag axis. This results in residual moveout in space-lag gathers (zero time-lag slice) and defocusing in time-lag gathers (zero space-lag slice). These phenomena are correlated, and they are a rich source of information for velocity model updates.

The extended image distortions caused by velocity model errors can be used to design velocity model building algorithms. When the extended image cones shift, the distance and direction of their apex away from zero time lag constrain model errors. This information can be used to construct an image perturbation, from which a slowness perturbation is inverted under the framework of linearized wave-equation migration velocity analysis. Alternatively, one can formulate a non-linear optimization problem to reconstruct the model by minimizing this image error. This approach requires the adjoint-state method to compute the gradient of the objective function, and iteratively update the model in the steepest-descent direction.

The space-lag subset of extended images has been used to reconstruct the velocity model by differential semblance optimization for a decade. The basis of the method is to penalize the defocusing in the gathers and to focus the reflection energy at zero lags by optimizing the model. The assumption that defocusing is caused by velocity model error is violated where the subsurface illumination is uneven. To improve the robustness and accuracy of the technique, the illumination compensation must be incorporated into the model building. The illumination compensation effectively isolates the defocusing due to uneven illumination or missing data. The key is to construct an illumination-based penalty operator by illumination analysis. Such a penalty automatically downweights the defocusing from illumination effects and allows the inversion to suffer less from the effects of uneven illumination and to take into account only the image error due to inaccurate velocity models.

One major issue for differential semblance optimization with space-lag gathers is the cost of computing and storing the gathers. To address the problem, extended space- and time-lag point gathers can be used as an alternative to the costlier common-image gathers. The point gathers are subsets of extended images constructed sparsely in subsurface on reflectors. The point gathers share similar reflection moveout characteristics with space-lag gathers, and thus differential semblance optimization can be implemented with such gathers. The point gathers reduce the computational and storage cost required by space-lag gathers especially in 3-D applications. Furthermore, the point gathers avoid the dip limitation in space-lag gathers and more accurately characterize the velocity information for steep reflections.

The rapid modeling and detection of earthquakes and transient deformation is a problem of extreme societal importance for earthquake early warning and rapid hazard response. To date, GPS data is not used in earthquake early warning or rapid source modeling even in Japan or California where the most extensive geophysical networks exist. This dissertation focuses on creating algorithms for automated modeling of earthquakes and transient slip events using GPS data in the western United States and Japan. First, I focus on the creation and use of high-rate GPS and combined seismogeodetic data for applications in earthquake early warning and rapid slip inversions. Leveraging data from earthquakes in Japan and southern California, I demonstrate that an accurate magnitude estimate can be made within seconds using P wave displacement scaling, and that a heterogeneous static slip model can be generated within 2-3 minutes. The preliminary source characterization is sufficiently robust to independently confirm the extent of fault slip used for rapid assessment of strong ground motions and improved tsunami warning in subduction zone environments. Secondly, I investigate the automated detection of transient slow slip events in Cascadia using daily positional estimates from GPS. Proper geodetic characterization of transient deformation is necessary for studies of regional interseismic, coseismic and postseismic tectonics, and miscalculations can affect our understanding of the regional stress field. I utilize the relative strength index (RSI) from financial forecasting to create a complete record of slow slip from continuous GPS stations in the Cascadia subduction zone between 1996 and 2012. I create a complete history of slow slip across the Cascadia subduction zone, fully characterizing the timing, progression, and magnitude of events. Finally, using a combination of continuous and campaign GPS measurements, I characterize the amount of extension, shear and subsidence in the Salton Trough, one of the most complex zone of active faulting and seismicity in California. I show the implications that faulting in the Salton Trough has for the evolution of the Brawley Seismic Zone, and more importantly, the southern San Andreas fault.

Long-offset, large-angle reflections have great potential for both both velocity and density inversion. Prestack migration has angle-dependent wavelet stretch effects, which lowers the image resolution at large reflection angles. Current stretch correction filters operate on migrated images. We develop a new stretch-free imaging condition, which does a shrink-and-shift operation on the extracted propagation wavelet after extrapolation, but before the imaging condition is applied. Most existing amplitude versus angle methods do modeling with Zoeppritz approximations, which lose accuracy at large angles. We develop a new inversion method using the "exact" Zoeppritz equation, which is able to invert up to 4 elastic parameters, comparing to the conventional 2- or 3-term inversion. Near- and post-critical reflections have phase shifts as well as amplitude increases. We propose using phase versus angle data (combined with the amplitude data) to do elastic inversion. Phase is less affected than amplitudes by the transmission losses, which makes it more accurate for a target with many overburden layers. The plane-wave reflection coefficients given by the Zoeppritz equation are not applicable near the critical angle in time-space domain, and the modeling of accurate spherical-wave reflection coefficients is expensive. The tau-p transform decomposes spherical waves into plane waves, and thus provides a way of applying the Zoeppritz equation to wide-angle reflections. We test the accuracy of forward modeling and develop a new target-oriented amplitude and phase versus angle inversion algorithm using a tau-p transform and ray tracing, which applies to laterally heterogeneous models. The ray tracing links the reflection angle at the target reflector and the apparent slowness at the receiver, which enables extracting the amplitude and phase versus angle data in the tau-p domain. We suggest using precritical amplitudes and postcritical phases in the tau-p domain for inversion, which uses the Zoeppritz equation to do efficient forward modeling, and can estimate the elastic parameters beneath the target reflector.