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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Case History : Using time-lapse vertical seismic profiling data to constrain velocity-saturation relations: the Frio brine pilot CO 2 injection: Time-lapse VSP to constrain VSRs

CO 2 sequestration projects benefit from quantitative assessment of saturation distribution and plume extent for field development and leakage prevention. In this work, we carry out quantitative analysis of time-lapse seismic by using rock physics and seismic modelling tools. We investigate the suitability of Gassmann's equation for a CO 2 sequestration project with 1600 tons of CO 2 injected into high-porosity, brine-saturated sandstone. We analyze the observed time delays and amplitude changes in a time-lapse vertical seismic profile dataset. Both reflected and transmitted waves are analyzed qualitatively and quantitatively. To interpret the changes obtained from the vertical seismic profile, we perform a 2.5D elastic, finite-difference modelling study. The results show a P-wave velocity reduction of 750 m/s in the proximity of the injection well evident by the first arrivals (travel-time delays and amplitude change) and reflected wave amplitude changes. These results do not match with our rock physics model using Gassmann's equation predictions even when taking uncertainty in CO 2 saturation and grain properties into account. We find that time-lapse vertical seismic profile data integrated with other information (e.g., core and well log) can be used to constrain the velocity–saturation relation and verify the applicability of theoretical models such as Gassmann's equation with considerable certainty. The study shows that possible nonelastic factors are in play after CO 2 injection (e.g., CO 2 –brine–rock interaction and pressure effect) as Gassmann's equation underestimated the velocity reduction in comparison with field data for all three sets of time-lapse vertical seismic profile attributes. Here, our work shows the importance of data integration to validate the applicability of theoretical models such as Gassmann's equation for quantitative analysis of time-lapse seismic data.

58 GEOSCIENCES↗
DOE OSTI2022

Quantitative interpretation of time-lapse seismic data at Farnsworth field unit: Rock physics modeling, and calibration of simulated time-lapse velocity responses

Here, this study investigates the contribution of fluid saturation variation to the time-lapse velocity response by performing fluid substitution modeling. The methodology is exemplified by the time-lapse seismic monitoring of carbon dioxide at Farnsworth field unit (FWU). In order to evaluate the fluid distribution in a matured oil reservoir, the Southwest Regional Partnership (SWP) acquired multiple vertical seismic profile (VSP) surveys at different times during the CO 2 –water alternatinggas (WAG) injection period. In this work, we present a thorough methodology for computing the elastic response of the saturated rock for different fluid saturations using a site-specific petro-elastic model (PEM). The output from the PEM was combined with results from a fluid compositional model to compute the seismic velocities at times corresponding to each VSP survey. To produce a calibrated simulated response, the measured time-lapse seismic velocities were integrated into the numerical simulation model. The mismatches between the predicted and measured time-lapse velocities were minimized through an iterative calibration process using a trained artificial neural network proxy (ANN) coupled with a particle swarm optimizer (PSO). Our study indicates that the hybrid optimization workflow can effectively perform the history matching. With an accurate prediction of the hydrodynamic properties, the migration of CO 2 within the subsurface was modeled by predicting the spatial velocity distribution for a radius of 305 m around the injection well. The technology demonstrated and the expertise gained from this study can guide similar CO 2 -WAG projects.

58 GEOSCIENCES↗
DOE OSTI2017

PFLOTRAN-E4D: A parallel open source PFLOTRAN module for simulating time-lapse electrical resistivity data

Time-lapse electrical resistivity tomography (ERT) is finding increased application for remotely monitoring processes occurring in the near subsurface in three-dimensions (i.e. 4D monitoring). However, there are few codes capable of simulating the evolution of subsurface resistivity and corresponding tomographic measurements arising from a particular process, particularly in parallel and with an open source license. Herein we describe and demonstrate an electrical resistivity tomography module for the PFLOTRAN subsurface simulation code, named PFLOTRAN-E4D. The PFLOTRAN-E4D module operates in parallel using a dedicated set of compute cores in a master-slave configuration. At each time step, the master processes receives subsurface states from PFLOTRAN, converts those states to bulk electrical conductivity, and instructs the slave processes to simulate a tomographic data set. The resulting multi-physics simulation capability enables accurate feasibility studies for ERT imaging, the identification of the ERT signatures that are unique to a given process, and facilitates the joint inversion of ERT data with hydrogeological data for subsurface characterization. PFLOTRAN-E4D is demonstrated herein using a field study of stage-driven groundwater/river water interaction ERT monitoring along the Columbia River, Washington, USA. Results demonstrate the complex nature of changes subsurface electrical conductivity, in both the saturated and unsaturated zones, arising from water table changes and from river water intrusion into the aquifer. The results also demonstrate the sensitivity of surface based ERT measurements to those changes over time. PFLOTRAN-E4D is available with the PFLOTRAN development version with an open-source license at https://bitbucket.org/pflotran/pflotran-dev .

Environmental Molecular Sciences Laboratory↗
DOE OSTI2020

Time-Lapse Gravity Monitoring of CO2 Migration Based on Numerical Modeling of a Faulted Storage Complex

In this study, the performance of both surface and borehole time-lapse gravity monitoring to detect CO2 leakage from a carbon storage site is evaluated. Several hypothetical scenarios of CO2 migration in a leaky fault, and thief zones at different depths at the Kimberlina site (California, USA) constitute the basis of the approach. The CO2 displacement is simulated using the TOUGH2 simulator applied to a detailed geological model of the site. The gravity responses to these CO2 plumes are simulated using forward modeling with sensors at ground surface and in vertical boreholes. Results of inversion on one scenario are also presented. The surface-based gravity responses obtained for the different leakage scenarios demonstrate that leakage can be detected at the surface in all the scenarios but the time to detection is highly variable (10 to 40 years) and dependent on the detection threshold considered. Borehole measurements of the vertical component of gravity provide excellent constrains in depth when they are located in proximity of the density anomaly associated with the presence of CO2, thus discriminating multiple leaks in different thief zones. Joint inversion of surface and borehole data can bring valuable information of the occurrence of leakages and their importance by providing a reasonable estimate of mass of displaced fluids. This study demonstrates the importance of combining multiphase flow simulations with gravity modeling in order to define if and when gravity monitoring would be applicable at a given storage site.

Time-lapse gravity monitoring, leak detection, CCS↗
DOE OSTI2020

Towards real-time monitoring: data assimilated time-lapse full waveform inversion for seismic velocity and uncertainty estimation

SUMMARY Rapid development of time-lapse seismic monitoring instrumentations has made it possible to collect dense time-lapse data for tomographically retrieving time-lapse (even continuous) images of subsurface changes. While traditional time-lapse full waveform inversion (TLFWI) algorithms are designed for sparse time-lapse surveys, they lack of effective temporal constraint on time-lapse data, and, more importantly, lack of the uncertainty estimation of the TLFWI results that is critical for further interpretation. Here, we propose a new data assimilation TLFWI method, using hierarchical matrix powered extended Kalman filter (HiEKF) to quantify the image uncertainty. Compared to existing Kalman filter algorithms, HiEKF allows to store and update a data-sparse representation of the cross-covariance matrices and propagate model errors without expensive operations involving covariance matrices. Hence, HiEKF is computationally efficient and applicable to 3-D TLFWI problems. Then, we reformulate TLFWI in the framework of HiEKF (termed hereafter as TLFWI-HiEKF) to predict time-lapse images of subsurface spatiotemporal velocity changes and simultaneously quantify the uncertainty of the inverted velocity changes over time. We demonstrate the validity and applicability of TLFWI–HiEKF with two realistic CO2 monitoring models derived from Frio-II and Cranfield CO2 injection sites, respectively. In both 2-D and 3-D examples, the inverted high-resolution time-lapse velocity results clearly reveal a continuous velocity reduction due to the injection of CO2. Moreover, the accuracy of the model is increasing over time by assimilating more time-lapse data while the standard deviation is decreasing over lapsed time. We expect TLFWI-HiEKF to be equipped with real-time seismic monitoring systems for continuously imaging the distribution of subsurface gas and fluids in the future large-scale CO2 sequestration experiments and reservoir management.

58 GEOSCIENCES↗
DOE OSTI2014

Monitoring CO 2 Storage at Cranfield, Mississippi with Time-Lapse Offset VSP – Using Integration and Modeling to Reduce Uncertainty

A time-lapse Offset Vertical Seismic Profile (OVSP) data set was acquired as part of a subsurface monitoring program for geologic sequestration of CO 2 . The storage site at Cranfield, near Natchez, Mississippi, is part of a detailed area study (DAS) site for geologic carbon sequestration operated by the U.S. Dept. of Energy’s Southeast Regional Carbon Sequestration Partnership (SECARB). The DAS site includes three boreholes, an injection well and two monitoring wells. The project team selected the DAS site to examine CO 2 sequestration multiphase fluid flow and pressure at the interwell scale in a brine reservoir. The time-lapse (TL) OVSP was part of an integrated monitoring program that included well logs, crosswell seismic, electrical resistance tomography and 4D surface seismic. The goals of the OVSP were to detect the CO 2 induced change in seismic response, give information about the spatial distribution of CO 2 near the injection well and to help tie the high-resolution borehole monitoring to the 4D surface data. The VSP data were acquired in well CFU 31-F1, which is the ~3200 m deep CO 2 injection well at the DAS site. A preinjection survey was recorded in late 2009 with injection beginning in December 2009, and a post injection survey was conducted in Nov 2010 following injection of about 250 kT of CO 2 . The sensor array for both surveys was a 50-level, 3-component, Sercel MaxiWave system with 15 m (49 ft) spacing between levels. The source for both surveys was an accelerated weight drop, with different source trucks used for the two surveys. Consistent time-lapse processing was applied to both data sets. Time-lapse processing generated difference corridor stacks to investigate CO 2 induced reflection amplitude changes from each source point. Corridor stacks were used for amplitude analysis to maximize the signal-to-noise ratio (S/N) for each shot point. Spatial variation in reflectivity (used to ‘map’ the plume) was similar in magnitude to the corridor stacks but, due to relatively lower S/N, the results were less consistent and more sensitive to processing and therefore are not presented. We examined the overall time-lapse repeatability of the OVSP data using three methods, the NRMS and Predictability (Pred) measures of Kragh and Christie (2002) and the signal-to-distortion ratio (SDR) method of Cantillo (2011). Because time-lapse noise was comparable to the observed change, multiple methods were used to analyze data reliability. The reflections from the top and base reservoir were identified on the corridor stacks by correlation with a synthetic response generated from the well logs. A consistent change in the corridor stack amplitudes from pre- to post-CO 2 injection was found for both the top and base reservoir reflections on all ten shot locations analyzed. In addition to the well-log synthetic response, a finite-difference elastic wave propagation model was built based on rock/fluid properties obtained from well logs, with CO 2 induced changes guided by time-lapse crosswell seismic tomography (Ajo-Franklin, et al., 2013) acquired at the DAS site. Time-lapse seismic tomography indicated that two reservoir zones were affected by the flood. The modeling established that interpretation of the VSP trough and peak event amplitudes as reflectivity from the top and bottom of reservoir is appropriate even with possible tuning effects. Importantly, this top/base change gives confidence in an interpretation that these changes arise from within the reservoir, not from bounding lithology. The modeled time-lapse change and the observed field data change from 10 shotpoints are in agreement for both magnitude and polarity of amplitude change for top and base of reservoir. Therefore, we conclude the stored CO 2 has been successfully detected and, furthermore, the observed seismic reflection change can be applied to Cranfield’s 4D surface seismic for spatially delineating the CO 2 /brine interface.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Data-assimilated time-lapse visco-acoustic full-waveform inversion: Theory and application for injected CO 2 plume monitoring

Continuous seismic monitoring for quantifying CO 2 plume migration and detection of any potential leakages in the subsurface is essential for the security of long-term anthropogenic carbon dioxide geologic storage. Traditional time-lapse full-waveform inversion (TLFWI) methods aim to map the CO 2 distribution by estimating seismic velocity changes, but recent studies find that CO 2 -induced attenuation is an important complement to seismic velocity for tracking the CO 2 plumes and even quantifying the CO 2 saturation. We have developed a novel data-assimilated TLFWI method to construct high-resolution time-lapse velocity and attenuation changes from dense time-lapse monitoring data. This method consists of two theoretical developments: visco-acoustic full-waveform inversion (QFWI) and multiparameter hierarchical matrix-powered extended Kalman filter (mHiEKF). The method is capable of (1) posing temporal constraints to retrieve time-lapse information from dense monitoring data by using mHiEKF, (2) accurately recovering high-spatial-resolution velocity and attenuation perturbations using first-order equation system-based QFWI, and (3) providing the model uncertainty by estimating their model standard deviation. With numerical examples, we first find the effectiveness of the new QFWI on estimating accurate velocity and attenuation models simultaneously. Then, a CO 2 leakage case and a realistic Frio-II CO 2 monitoring case are presented to find the advantages and applicability of our data-assimilated QFWI method for estimating time-lapse changes using dense time-lapse monitoring surveys. Here, by assimilating time-lapse seismic monitoring data over time, our data-assimilated QFWI method can improve the resolution of velocity and attenuation changes and decrease their model uncertainties.

58 GEOSCIENCES↗
DOE OSTI2013

Assessing Uncertainty and Repeatability in Time-Lapse VSP Monitoring of CO2 Injection in a Brine Aquifer, Frio Formation, Texas (A Case Study)

This study was done to assess the repeatability and uncertainty of time-lapse VSP response to CO 2 injection in the Frio formation near Houston Texas. A work flow was built to assess the effect of time-lapse injected CO 2 into two Frio brine reservoir intervals, the ‘C’ sand (Frio1) and the ‘Blue sand’ (Frio2). The time-lapse seismic amplitude variations with sensor depth for both reservoirs Frio1 and Frio2 were computed by subtracting the seismic response of the base survey from each of the two monitor seismic surveys. Source site 1 has been considered as one of the best sites for evaluating the time-lapse response after injection. For site 1, the computed timelapse NRMS levels after processing had been compared to the estimated time-lapse NRMS level before processing for different control reflectors, and for brine aquifers Frio1, and Frio2 to quantify detectability of amplitude difference. As the main interest is to analyze the time-lapse amplitude variations, different scenarios have been considered. Three different survey scenarios were considered: the base survey which was performed before injection, monitor1 performed after the first injection operation, and monitor2 which was after the second injection. The first scenario was base-monitor1, the second was basemonitor2, and the third was monitor1-monitor2. We considered three ‘control’ reflections above the Frio to assist removal of overburden changes, and concluded that third control reflector (CR3) is the most favorable for the first scenario in terms of NRMS response, and first control reflector (CR1) is the most favorable for the second and third scenarios in terms of NRMS response. The NRMS parameter is shown to be a useful measure to assess the effect of processing on time-lapse data. The overall NRMS for the Frio VSP data set was found to be in the range of 30% to 80% following basic processing. This could be considered as an estimated baseline in assessing the utility of VSP for CO 2 monitoring. This study shows that the CO 2 injection in brine reservoir Frio1 (the ‘C’ sand unit) does induce a relative change in amplitude response, and for Frio2 (the ‘Blue’ sand unit) an amplitude change has been also detected, but in both cases the uncertainty, as measured by NRMS indicates the reservoir changes are, at best, only slightly above the noise level, and often below the noise level of the overall data set.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Time-Lapse Integration at FWU: Fluids, Rock Physics, Numerical Model Integration, and Field Data Comparison

We present the current status of time-lapse seismic integration at the Farnsworth (FWU) CO2 WAG (water-alternating-gas) EOR (Enhanced Oil Recovery) project at Ochiltree County, northwest Texas. As a potential carbon sequestration mechanism, CO2 WAG projects will be subject to some degree of monitoring and verification, either as a regulatory requirement or to qualify for economic incentives. In order to evaluate the viability of time-lapse seismic as a monitoring method the Southwest Partnership (SWP) has conducted time-lapse seismic monitoring at FWU using the 3D Vertical Seismic Profiling (VSP) method. The efficacy of seismic time-lapse depends on a number of key factors, which vary widely from one application to another. Most important among these are the thermophysical properties of the original fluid in place and the displacing fluid, followed by the petrophysical properties of the rock matrix, which together determine the effective elastic properties of the rock fluid system. We present systematic analysis of fluid thermodynamics and resulting thermophysical properties, petrophysics and rock frame elastic properties, and elastic property modeling through fluid substitution using data collected at FWU. These analyses will be framed in realistic scenarios presented by the FWU CO2 WAG development. The resulting fluid/rock physics models will be applied to output from the calibrated FWU compositional reservoir simulation model to forward model the time-lapse seismic response. Modeled results are compared with field time-lapse seismic measurements and strategies for numerical model feedback/update are discussed. While mechanical effects are neglected in the work presented here, complementary parallel studies are underway in which laboratory measurements are introduced to introduce stress dependence of matrix elastic moduli.

4D↗
DOE OSTI2022

Time-lapse seismic data inversion for estimating reservoir parameters using deep learning

Geologic carbon sequestration involves the injection of captured carbon dioxide ([Formula: see text]) into subsurface formations for long-term storage. The movement and fate of the injected [Formula: see text] plume is of great concern to regulators because monitoring helps to identify potential leakage zones and determines the possibility of safe long-term storage. To address this concern, we design a deep-learning framework for [Formula: see text] saturation monitoring to determine the geologic controls on the storage of the injected [Formula: see text]. We use different combinations of porosities and permeabilities for a given reservoir to generate saturation and velocity models. We train the deep-learning model with a few time-lapse seismic images and their corresponding changes in saturation values for a particular [Formula: see text] injection site. The deep-learning model learns the mapping from the change in the time-lapse seismic response to the change in [Formula: see text] saturation during the training phase. We then apply the trained model to data sets comprising different time-lapse seismic image slices (corresponding to different time instances) generated using different porosity and permeability distributions that are not part of the training to estimate the [Formula: see text] saturation values along with the plume extent. Our algorithm provides a deep-learning assisted framework for the direct estimation of [Formula: see text] saturation values and plume migration in heterogeneous formations using the time-lapse seismic data. Our method improves the efficiency of time-lapse inversion by streamlining the large number of intermediate steps in the conventional time-lapse inversion workflow. This method also helps to incorporate the geologic uncertainty for a given reservoir by accounting for the statistical distribution of porosity and permeability during the training phase. Tests on different examples verify the effectiveness of our approach.

Geochemistry & Geophysics↗
DOE OSTI2020

Numerical Modeling of Anisotropic Elastic-Wave Sensitivity Propagation for Optimal Design of Time-Lapse Seismic Surveys

Reliable subsurface time-lapse seismic monitoring is crucial for many geophysical applications, such as enhanced geothermal system characterization, geologic carbon utilization and storage, and conventional and unconventional oil/gas reservoir characterization, etc. In this work, we develop an elastic-wave sensitivity propagation method for optimal design of cost-effective time-lapse seismic surveys considering the fact that most of subsurface geologic layers and fractured reservoirs are anisotropic instead of isotropic. For anisotropic media, we define monitoring criteria using qP- and qS-wave sensitivity energies after decomposing qP- and qS-wave components from the total elastic-wave sensitivity wavefield using a hybrid time- and frequency-domain approach. Geophones should therefore be placed at locations with significant qP- and qS-wave sensitivity energies for cost-effective time-lapse seismic monitoring in an anisotropic geology setting. Our numerical modeling results for a modified anisotropic Hess model demonstrate that, compared with the isotropic case, subsurface anisotropy changes the spatial distributions of elastic-wave sensitivity energies. Consequently, it is necessary to consider subsurface anisotropies when designing the spatial distribution of geophones for cost-effective time-lapse seismic monitoring. This finding suggests that it is essential to use our new anisotropic elastic-wave sensitivity modeling method for optimal design of time-lapse seismic surveys to reliably monitor the changes in subsurface reservoirs, fracture zones or target monitoring regions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Modeling of time-lapse seismic monitoring using CO 2 leakage simulations for a model CO 2 storage site with realistic geology: Application in assessment of early leak-detection capabilities

Time-lapse surface seismic surveys have been widely used at carbon sequestration sites for site characterization, monitoring subsurface CO 2 plume migration, and detecting potential CO 2 leakage from a storage reservoir. Monitoring in the first permeable unit directly above the primary seal is important for early detection of CO 2 leakage. Forward modeling of time-lapse seismic data can be used to assess the utility of the seismic method for CO 2 leakage detection. We develop a workflow for forward modeling of time-lapse seismic data, including constructing seismic velocity models using flow simulation outputs, modeling of pre-stack and post-stack synthetic seismic data following seismic data processing sequence and analysis of processed synthetic time-lapse seismic data. We apply the forward modeling and analysis workflow to assessing the detectability and the earliest detection time of seismic monitoring using the hypothetical CO 2 leakage scenarios for a model geologic storage site with realistic geology. We then derive the detection thresholds using the simulated normalized root-mean-square (NRMS) differences for the no-leakage case at a range of signal-to-noise ratios, representing the background noise levels in seismic data. We then compare NRMS differences triggered by the CO 2 leakage to the detection thresholds at each time step to quantify the detectability and the earliest detection time of seismic monitoring. We analyze the effects of the acquisition parameters and elastic parameters on the produced synthetic seismic data and earliest detection time. Our modeling results indicate that high signal-to-noise ratio is needed to detect the CO 2 leakage at the model site. Minimizing the background noise in seismic data is crucial for improving the detectability of the seismic method. Increasing the shot density or increasing the dominant frequency of the source wavelet is likely to increase the possibility of the leakage detection and reduce the time needed for the detection. The elastic parameters used in the rock physics modeling have significant effects on the resultant seismic velocity models and synthetic seismic data, highlighting their critical roles in understanding and interpreting time-lapse seismic reflection data associated with CO 2 monitoring, verification and accounting activities.

58 GEOSCIENCES↗
DOE OSTI2025

On the lapse contour in the gravitational path integral

The gravitational path integral is usually implemented with a covariant action by analogy with other gauge field theories, but the gravitational case is different in important ways. A key difference is that the integrand has an essential singularity, which occurs at zero lapse where the spacetime metric degenerates. The lapse integration contour required to impose the local time reparametrization constraints must run from − ∞ to + ∞ , yet must not pass through zero. This raises the question: for an application—such as a partition function—where the constraints should be imposed, what is the correct integration contour, and why? We study that question by starting with the reduced phase space path integral, which involves no essential singularity. We observe that if the momenta are to be integrated before the lapse, to obtain a configuration space path integral, the lapse contour should pass below the origin in the complex lapse plane. This contour is also consistent with the requirement that quantum field fluctuation amplitudes have the usual short distance vacuum form, and with obtaining the Bekenstein-Hawking horizon entropy from a Lorentzian path integral. Published by the American Physical Society 2025

Banihashemi, Batoul (ORCID:0000000228679209)↗
DOE OSTI2021

Stepwise Dynamic Calibration of a Hydromechanical Simulation Using Time-Lapse Vertical Seismic Profile

This study aims to develop a methodology for calibrating subsurface stress changes through time-lapse Vertical Seismic Profiling (VSP) integration. The selected study site is the 13-10A injector well within the ongoing CO2-EOR operation of the Farnsworth Field Unit. The Time-lapse VSP dataset carries the combined effects of fluid substitution and mean effective stress changes, thereby providing a dataset amenable for the calibration of production and injection-induced stress changes. The concept is similar to calibrating a reservoir simulation model in that the process honor real field data to set up an inverse problem. The solution optimizes the independent and impactful geomechanical parameters that replicate the observed time-lapse seismic velocity changes. This stress calibration is enabled by 4D geomechanical modeling and the VSP Integration workflow. This calibration benefits from extensive geological, geophysical and geomechanical characterization through 3D seismic data, geophysical well logs, and core assessed as part of the 1D MEM conducted on the 13-10A subject well. These data are used to develop a site-specific rock physics model. The Biot Gassmann workflow combines rock physics and reservoir simulation outputs to determine the fluid substitution contribution to seismic velocity change. Additionally, modeled seismic velocity attributed to mean effective stress are determined from the geomechanical simulation outputs, and the stress-velocity relationship developed from the ultrasonic seismic velocity measurements on the extracted Morrow B core. A penalty function is then formed between the modeled seismic velocities and the observed time-lapse VSP dataset. Four independent and impactful geomechanical parameters have been determined. These are the bulk modulus and shear modulus for zero porosity and the shear and compressional seismic velocity to mean effective stress derivatives. The dataset of numerous coupled hydromechanical- geomechanical simulation realizations is built by combining variations of the four stated geomechanical parameters. A machine learning-assisted workflow comprised of an artificial neural network and a particle swarm optimizer are used to converge on the optimal geomechanical parameters. The successful execution of this workflow has affirmed the suitability of acoustic time-lapse measurements for 4D-VSP geomechanical stress calibration pending measurable stress sensitivities within the anticipated effective stress changes and the availability of suitable and reliable datasets for petroelastic modeling.

02 PETROLEUM↗