This thesis describes new interferometric imaging methods for migration and waveform inversion. The key idea is to use reflection events from a known reference reflector to ”naturally redatum” the receivers and sources to the reference reflector. Here, ”natural redatuming” is a data-driven process where the redatuming Green’s functions are obtained from the data. Interferometric imaging eliminates the statics associated with the noisy overburden above the reference reflector. To mitigate the defocussing caused by overburden errors I first propose the use of interferometric least-squares migration (ILSM) to estimate the migration image. Here, a known reflector is used as the reference interface for ILSM, and the data are naturally redatumed to this reference interface before imaging. Numerical results on synthetic and field data show that ILSM can significantly reduce the defocussing artifacts in the migration image. Next, I develop a waveform tomography approach for inverting the velocity model by mitigating the velocity errors in the overburden. Unresolved velocity errors in the overburden velocity model can cause conventional full-waveform inversion to get stuck in a local minimum. To resolve this problem, I present interferometric full-waveform inversion (IFWI), where conventional waveform tomography is reformulated so a velocity model is found that minimizes the objective function with an interferometric crosscorrelogram misfit. Numerical examples show that IFWI, compared to FWI, computes a significantly more accurate velocity model in the presence of a nearsurface with unknown velocity anomalies. I use IFWI and ILSM for 4D imaging where seismic data are recorded at different times over the same reservoir. To eliminate the time-varying effects of the near surface both data sets are virtually redatumed to a common reference interface before migration. This largely eliminates the overburden-induced statics errors in both data sets. Results with synthetic and field data show that ILSM and IFWI can suppress the artifacts caused by non-repeatability in time-lapse surveys. This can lead to a much more accurate characterization of the movement of fluids over time. In turn, this information can be used to optimize the extraction of resources in enhanced oil recovery (EOR) operations.

Master of Science / Department of Geology / Abdelmoneam Raef / Advancements, applications, and success of time-lapse (4D) seismic monitoring of carbonate reservoirs is limited by these systems’ inherent heterogeneity and low compressibility relative to siliciclastic systems. To contribute to the advancement of 4D seismic monitoring in carbonates, an investigation of amplitude envelope across frequency sub-bands was conducted on a high-resolution 4D seismic data set acquired in fine temporal intervals between a baseline and eight monitor surveys to track CO₂-EOR from 2003-2005 in the Hall-Gurney Field, Kansas. The shallow (approximately 900 m) Plattsburg ‘C Zone’ target reservoir is an oomoldic limestone within the Lansing-Kansas City (LKC) supergroup – deposited as a sequence of high-frequency, stacked cyclothems. The LKC reservoir fluctuates around thin-bed thickness within the well pattern region and is susceptible to amplitude tuning effects, in which CO₂ replacement of initial reservoir fluid generates a complex tuning phenomena with reduction and brightening of amplitude at reservoir thickness above and below thin-bed thickness, respectively. A thorough analysis of horizon snapping criteria and parameters was conducted to understand the sensitivity of these autonomous operations and produce a robust horizon tracking workflow to extend the Baseline Survey horizon data to subsequent Monitor Surveys. This 4D seismic horizon tracking workflow expedited the horizon tracking process across monitor surveys, while following a quantitative, repeatable approach in tracking the LKC and maintaining geologic integrity despite low signal-to-noise ratio (SNR) data and misties between surveys. Analysis of amplitude envelope data across frequency sub-bands (30-80 Hz) following spectral decomposition identified geometric features of multiple LKC shoal bodies at the reservoir interval. In corroboration with prior geologic interpretation, shoal boundaries, zones of overlap between stacked shoals, thickness variation, and lateral changes in lithofacies were delineated in the Baseline Survey, which enhanced detail of these features’ extent beyond capacity offered from well log data. Lineaments dominated by low-frequency anomalies within regions of adjacent shoals’ boundaries suggest thicker zones of potential shoal overlap. Analysis of frequency band-to-band analysis reveals relative thickness variation. Spectral decomposition of the amplitude envelope was analyzed between the Baseline and Monitor Surveys to identify spectral and tuning changes to monitor CO₂ migration. Ambiguity of CO₂ effects on tuning phenomena was observed in zones of known CO₂ fluid replacement. A series of lineaments highlighted by amplitude brightening from the Baseline to Monitor Surveys is observed, which compete with a more spatially extensive effect of subtle amplitude dimming. These lineaments are suggestive of features below tuning thickness, such as stratigraphic structures of shoals, fractures, and/or thin shoal edges, which are highlighted by an increased apparent thickness and onset of tuning from CO₂. Detailed analysis of these 4D seismic data across frequency sub-bands provide enhanced interpretation of shoal geometry, position, and overlap; identification of lateral changes in lithofacies suggestive of barriers and conduits; insight into relative thickness variation; and the ability of CO₂ tuning ambiguity to highlight zones below tuning thickness and improve reservoir characterization. These results suggest improved efficiency of CO₂ -EOR reservoir surveillance in carbonates, with implications to ensure optimal field planning and flood performance for analogous targets.

Time-lapse seismic monitoring repeats 3D seismic imaging over a reservoir to map fluid movements in a reservoir. During hydrocarbon production, the fluid saturation, pressure, and temperature of a reservoir change, thereby altering the acoustic properties of the reservoir. Time-lapse seismic analysis can illuminate these dynamic changes of reservoir properties, and therefore has strong potential for improving reservoir management. However, the response of a reservoir depends on many parameters and can be diffcult to understand and predict. Numerical modeling results integrating streamline fluid flow simulation, rock physics, and ray-Born seismic modeling address some of these problems. Calculations show that the sensitivity of amplitude changes to porosity depend on the type of sediment comprising the reservoir. For consolidated rock, high-porosity models show larger amplitude changes than low porosity models. However, in an unconsolidated formation, there is less consistent correlation between amplitude and porosity. The rapid time-lapse modeling schemes also allow statistical analysis of the uncertainty in seismic response associated with poorly known values of reservoir parameters such as permeability and dry bulk modulus. Results show that for permeability, the maximum uncertainties in time-lapse seismic signals occur at the water front, where saturation is most variable. For the dry bulk-modulus, the uncertainty is greatest near the injection well, where the maximum saturation changes occur. Time-lapse seismic methods can also be applied to monitor CO2 sequestration. Simulations show that since the acoustic properties of CO2 are very different from those of hydrocarbons and water, it is possible to image CO2 saturation using seismic monitoring. Furthermore, amplitude changes after supercritical fluid CO2 injection are larger than liquid CO2 injection. Two seismic surveys over Teal South Field, Eugene Island, Gulf of Mexico, were acquired at different times, and the numerical models provide important insights to understand changes in the reservoir. 4D seismic differences after cross-equalization show that amplitude dimming occurs in the northeast and brightening occurs in the southwest part of the field. Our forward model, which integrates production data, petrophysicals, and seismic wave propagation simulation, shows that the amplitude dimming and brightening can be explained by pore pressure drops and gas invasion, respectively.

Seismic data have been established as a valuable source of information for the construction of reservoir simulation models, most commonly for determination of the modeled geologic structure, and also for population of static petrophysical properties (e.g. porosity, permeability). More recently, the availability of repeated seismic surveys over the time scale of years (i.e., 4D seismic) has shown promising results for the qualitative determination of changes in fluid phase distributions and pressure required for determination of areas of bypassed oil, swept volumes and pressure maintenance mechanisms. Quantitatively, and currently the state of the art in reservoir model characterization, 4D seismic data have proven distinctively useful for the calibration of geologic spatial variability which ultimately contributes to the improvement of reservoir development and management strategies. Among the limited variety of techniques for the integration of dynamic seismic data into reservoir models, streamline-based techniques have been demonstrated as one of the more efficient approaches as a result of their analytical sensitivity formulations. Although streamline techniques have been used in the past to integrate time-lapse seismic attributes, the applications were limited to the simplified modeling scenarios of two-phase fluid flow and invariant streamline geometry throughout the production schedule. This research builds upon and advances existing approaches to streamline-based seismic data integration for the inclusion of both production and seismic data under varying field conditions. The proposed approach integrates data from reservoirs under active reservoir management and the corresponding simulation models can be constrained using highly detailed or realistic schedules. Fundamentally, a new derivation of seismic sensitivities is proposed that is able to represent a complex reservoir evolution between consecutive seismic surveys. The approach is further extended to manage compositional reservoir simulation with dissolution effects and gravity-convective-driven flows which, in particular, are typical of CO2 transport behavior following injection into deep saline aquifers. As a final component of this research, the benefits of dynamic data integration on the determination of swept and drained volumes by injection and production, respectively, are investigated. Several synthetic and field reservoir modeling scenarios are used for an extensive demonstration of the efficacy and practical feasibility of the proposed developments.

One of the most challenging tasks in the oil industry is the production of reliable reservoir forecast models. Because of different sources of uncertainties the numerical models employed are often only crude approximations of the reality. This problem is tackled by the conditioning of the model with production data through data assimilation. This process is known in the oil industry as history matching. Several recent advances are being used to improve history matching reliability, notably the use of time-lapse seismic data and automated history matching software tools. One of the most promising data assimilation techniques employed in the oil industry is the ensemble Kalman filter (EnKF) because its ability to deal with highly non-linear models, low computational cost and easy computational implementation when compared with other methods. A synthetic reservoir model was used in a history matching study designed to predict the peak production allowing decision makers to properly plan field development actions. If only production data is assimilated, a total of 12 years of historical data is required to properly characterize the production uncertainty and consequently the correct moment to take actions and decommission the field. However if time-lapse seismic data is available this conclusion can be reached 4 years in advance due to the additional fluid displacement information obtained with the seismic data. Production data provides geographically sparse data in contrast with seismic data which are sparse in time. Several types of seismic attributes were tested in this study. Poisson’s ratio proved to be the most sensitive attribute to fluid displacement. In practical applications, however the use of this attribute is usually avoided due to poor quality of the data. Seismic impedance tends to be more reliable. Finally, a new conceptual idea was proposed to obtain time-lapse information for a history matching study. The use of crosswell time-lapse seismic tomography to map velocities in the interwell region was demonstrated as a potential tool to ensure survey reproducibility and low acquisition cost when compared with full scale surface surveys. This approach relies on the higher velocity sensitivity to fluid displacement at higher frequencies. The velocity effects were modeled using the Biot velocity model. This method provided promising results leading to similar RRMS error reductions when compared with conventional history matched surface seismic data.

Seismic inversion is the leading method to map and quantify changes in time-lapse (4D) seismic datasets, with applications ranging from monitoring hydrocarbon-producing fields to geological CO2 storage. However, the process of inverting seismic data for reservoir properties is a notoriously ill-posed inverse problem due to the band-limited and noisy nature of seismic data. This comes with additional challenges for 4D applications, given the inaccuracies in the repeatability of time-lapse acquisition surveys. Consequently, adding prior information to the inversion process in the form of properly crafted regularization terms is essential to obtain geologically meaningful subsurface models and 4D effects. In this thesis, I propose a joint inversion-segmentation algorithm for 4D seismic inversion, which integrates total variation and segmentation priors as a way to counteract the missing frequencies and noise present in 4D seismic data. I validate the algorithm with synthetic and field seismic datasets and benchmark it against state-of-the-art 4D inversion techniques. The proposed algorithm shows three main advantages: 1. it produces high-resolution baseline and monitor acoustic impedance models, 2. by leveraging similarities between multiple seismic datasets, the proposed algorithm mitigates the non-repeatable noise and better highlights the real seismic time-lapse changes, and 3. it simultaneously provides a volumetric classification of the acoustic impedance 4D difference model based on user-defined classes, i.e., percentages of seismic time-lapse changes. Such advantages may enable more robust stratigraphic/structural and quantitative 4D seismic interpretation and provide more accurate inputs for dynamic reservoir simulations.