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Results
ABSTRACT Distributed-acoustic-sensing (DAS) fibers have enabled various geophysical applications in unconventional reservoirs. Combined with perforation shots, a DAS fiber can record valuable guided waves that propagate in the reservoir formation and carry information about its properties. However, the representation of perforation shots as seismic sources, needed to conduct quantitative analysis, remains unknown. We model such sources using a superposition of three mechanisms for which we derive the moment-tensor (MT) representation. Using field DAS data recorded in the same well where the perforations are located, we establish a workflow to invert the resolvable components of the total MT for 100 different perforation shots. By scrutinizing the inversion results, we conjecture that the MT can indicate how effectively a perforation shot creates microcracks in the surrounding rock. Furthermore, we observe a regular spatial pattern in the inverted MTs, which correlates with the relative location of the perforation shot within each stimulation stage.
- Geology > Geological Subdiscipline (0.47)
- Geology > Structural Geology > Tectonics (0.46)
ABSTRACT Producing reliable acoustic subsurface velocity models still remains the main bottleneck of the oil and gas industry’s traditional imaging sequence. In complex geologic settings, the output of conventional ray-based or wave-equation-based tomographic methods may not be sufficiently accurate for full-waveform inversion (FWI) to converge to a geologically satisfactory earth model. We create a new method referred to as full-waveform inversion by model extension (FWIME) in which a wave-equation migration velocity analysis (WEMVA) technique is efficiently paired with a modified version of FWI. We find that our method is more powerful than applying WEMVA and FWI sequentially, and that it can converge to accurate solutions without the use of a good initial guess or low-frequency energy. We determine FWIME’s potential on five realistic and challenging numerical examples that simulate complex geologic scenarios often encountered in hydrocarbon exploration. We guide the reader step by step throughout the optimization process. We find that our method can simultaneously invert all wave types with the same simple mechanism and without the need for a user-intensive hyperparameter tuning process. In an open-source online repository, we provide our C++/compute unified device architecture (CUDA) numerical implementation accelerated with graphics processing units, encapsulated in a Python interface. All the numerical examples developed are accessible through Python notebooks and fully reproducible.
ABSTRACT We describe a new method, full-waveform inversion by model extension (FWIME), that recovers accurate acoustic subsurface velocity models from seismic data when conventional methods fail. We leverage the advantageous convergence properties of wave equation migration velocity analysis (WEMVA) with the accuracy and high-resolution nature of acoustic full-waveform inversion (FWI) by combining them into a robust mathematically consistent workflow with minimal need for user inputs. The novelty of FWIME resides in the design of a new cost function and a novel optimization strategy to combine the two techniques, making our approach more efficient and powerful than applying them sequentially. We observe that FWIME mitigates the need for accurate initial models and low-frequency long-offset data, which can be challenging to acquire. Our new objective function contains two components. First, we modify the forward mapping of the FWI problem by adding a data-correcting term computed with an extended demigration operator, whose goal is to ensure phase matching between predicted and observed data, even when the initial model is inaccurate. The second component, which is a modified WEMVA cost function, allows us to progressively remove the contributions of the data-correcting term throughout the inversion process. The coupling between the two components is handled by the variable projection method, which reduces the number of adjustable hyperparameters, thereby making our solution simple to use. We devise a model-space multiscale optimization scheme by reparameterizing the velocity model on spline grids to control the resolution of the model updates. We generate three cycle-skipped 2D synthetic data sets, each containing only one type of wave (transmitted, reflected, or refracted), and we analyze how FWIME successfully recovers accurate solutions with the same procedure for all three cases. In a second paper, we apply FWIME to challenging realistic examples where we simultaneously invert all wave modes.
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic modeling (1.00)
- Data Science & Engineering Analytics > Information Management and Systems > Artificial intelligence (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Optimization (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Search (0.92)
- Information Technology > Artificial Intelligence > Machine Learning (0.67)
- Information Technology > Information Management > Search (0.67)
Advancements in geophysical inverse problem-solving are crucial for extracting reliable information and quantifying uncertainties. Traditional regularization techniques are instrumental in stabilizing these ill-posed problems, imposing additional constraints to control solution non-uniqueness. Embracing deep learning capabilities, we introduce an innovative strategy that incorporates neural network-based regularizers to boost the accuracy of Dix inversion with synthetic and field RMS velocity data. This approach confines the model possibilities to only plausible geological scenarios and helps rule out incoherent interval velocity models. Application to synthetic and North Sea field data has shown improved resolution and the inclusion of high-wavenumber content, enabling better resolvability of velocity changes across lithological boundaries. Looking ahead, we aim to extend this approach to Full Waveform Inversion (FWI) and explore the potential of a promising three-parameter input regularizer term.
- Europe > United Kingdom > North Sea (0.25)
- Europe > Norway > North Sea (0.25)
- Europe > North Sea (0.25)
- (2 more...)
- Geology > Rock Type (0.34)
- Geology > Geological Subdiscipline (0.31)
ABSTRACT Elastic full-waveform inversion (FWI) can provide accurate and high-resolution subsurface parameters. However, its high computational cost prevents the application of this method to large-scale field-data scenarios. To mitigate this limitation, we have developed a target-oriented elastic FWI methodology based on a redatuming step that relies upon an extended least-squares migration process. In our approach, the surface-reflection data can be attributed to a given subsurface portion when mapped into the image space. This process allows us to reconstruct reflection data generated by a target area and recorded with a virtual acquisition geometry positioned directly above it. The redatuming step enables the application of an elastic FWI method within the target portion only. The entire workflow drastically decreases the overall cost of the surface-data inversion and allows the retrieval of accurate elastic parameters of the area of interest. We determine the effectiveness of our approach on a synthetic case based on the well-known Marmousi2 model and on 3D ocean-bottom node pressure data recorded in the Gulf of Mexico in which we retrieve the elastic parameters of a potential prospect, positioned in proximity of a salt-dome flank, and whose rock-physical properties are consistent with the presence of a gas-bearing sand reservoir.
- North America > United States > California (0.46)
- Europe > United Kingdom > North Sea (0.28)
- Geology > Geological Subdiscipline (1.00)
- Geology > Structural Geology > Tectonics > Salt Tectonics (0.67)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (0.48)
- Geophysics > Seismic Surveying > Surface Seismic Acquisition > Marine Seismic Acquisition (1.00)
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling > Seismic Inversion (1.00)
- Geophysics > Seismic Surveying > Seismic Interpretation (1.00)
- Europe > United Kingdom > North Sea > Central North Sea > Moray Firth > Moray Firth Basin > Moray Firth Basin > Witch Ground Graben > P.213 > Block 16/26a > Brae Field > Alba Field > Caran Sandstone Formation (0.99)
- Europe > United Kingdom > North Sea > Central North Sea > Moray Firth > Moray Firth Basin > Moray Firth Basin > Witch Ground Graben > P.213 > Block 16/26a > Brae Field > Alba Field > Alba Sandstone Formation (0.99)
- Europe > United Kingdom > North Sea > Central North Sea > Moray Firth > Moray Firth Basin > Fladen Ground Spur > Witch Ground Graben > P.213 > Block 16/26a > Brae Field > Alba Field > Caran Sandstone Formation (0.99)
- (10 more...)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic modeling (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
- Data Science & Engineering Analytics > Information Management and Systems (1.00)
ABSTRACT The ability to create subsurface images whose amplitudes are proportional to the elastic wavefield variations recorded within seismic data as a function of reflection angle is fundamental for performing accurate amplitude-variation-with-offset (AVO) analysis and inversion. A process that generates such images is commonly referred to as true-amplitude migration. We have determined how the extended subsurface-offset image space is able to preserve the elastic behavior of the primary reflections when these events are acoustically migrated with a reverse time migration approach performed in a least-squares fashion. Using a single-interface model, we determine how the angle-domain image amplitude variations from an extended-offset acoustically migrated image closely follow the theoretical elastic Zoeppritz response even at the critical angle. Furthermore, we develop a subsalt synthetic test in which 1C ocean-bottom-node (OBN) data are used within a regularized linearized waveform inversion procedure. In this test, we highlight the ability of the acoustic extended-angle image domain to preserve the correct elastic amplitude variations of the reflected events from three subsalt sand lenses. Our method allows accurate inversion of elastic-wave data for subsurface parameter variations that are critical for reservoir characterization in oil and gas exploration and production. We determine its performance on an OBN field data set recorded in the Gulf of Mexico in which the AVO response of a potential gas-bearing prospect is correctly retrieved.
- Asia > Kazakhstan > West Kazakhstan > Precaspian Basin (0.99)
- Asia > Kazakhstan > Mangystau Oblast > Precaspian Basin (0.99)
- Asia > Kazakhstan > Atyrau > Precaspian Basin (0.99)
- (2 more...)
In the five years since we started the Stanford DAS-array project substantial progress have been made towards the goal of deploying city-wide dark-fiber seismic arrays that have the potential for improving the quality and safety of urban life. Four applications are the most promising: 1) nearsurface imaging and monitoring, 2) local-seismicity analysis, 3) traffic monitoring, and 4) infrastructure monitoring. Scaling up current small research arrays to citywide arrays is crucial for all of these applications to deliver real practical value. DAS interrogators improvements in range and sensitivity are decreasing unit-length cost and logistic challenges of large-scale deployments. Timely delivery of valuable information depends on developments of fast and automatic algorithms, such as neural networks running on cost-efficient hardware. Further progress are also necessary in specialized technologies such as the mapping of DAS virtual channels to physical locations, and fast signalenhancement methods.
We apply a target-oriented elastic full-waveform inversion (FWI) algorithm to the pressure component of an ocean-bottom-node (OBN) field dataset acquired in the Gulf of Mexico. Our target-oriented approach is based on a redatuming technique in which an extended image is employed to synthesize data as if the acquisition geometry was placed in proximity of a subsurface target. This extended image is obtained using a least-squares linear inversion process. The redatuming step allows us to limit the elastic FWI process within the target area only, which in turn results in a substantial computational speed-up factor compared to the elastic inversion of the original dataset. We demonstrate the efficacy of the proposed technique by estimating the elastic properties of a potential hydrocarbon prospect located on the flank of a salt diapir. The retrieved elastic properties are then used to estimate common rock-physics attributes that highlight the potential presence of a gas-bearing sand reservoir.
- North America > United States (0.25)
- North America > Mexico (0.25)
- Geology > Geological Subdiscipline > Geomechanics (0.91)
- Geology > Structural Geology > Tectonics > Salt Tectonics (0.57)
- Asia > Kazakhstan > West Kazakhstan > Precaspian Basin (0.99)
- Asia > Kazakhstan > Mangystau Oblast > Precaspian Basin (0.99)
- Asia > Kazakhstan > Atyrau > Precaspian Basin (0.99)
- (2 more...)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic modeling (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
Approximate Bayesian inference of seismic velocity and pore-pressure uncertainty with basin modeling, rock physics, and imaging constraints
Pradhan, Anshuman (Stanford University) | Dutta, Nader C. (Stanford University) | Le, Huy Q. (Stanford University) | Biondi, Biondo (Stanford University) | Mukerji, Tapan (Stanford University, Stanford University, Stanford University)
ABSTRACT We have introduced a methodology for quantifying seismic velocity and pore-pressure uncertainty that incorporates information regarding the geologic history of a basin, rock physics, well log, drilling, and seismic data. In particular, our approach relies on linking velocity models to the basin modeling outputs of porosity, mineral volume fractions, and pore pressure through rock-physics models. We account for geologic uncertainty by defining prior probability distributions on lithology-specific porosity compaction model parameters, permeability-porosity model parameters, and heat-flow boundary condition. Monte Carlo basin simulations are performed by sampling the prior uncertainty space. We perform probabilistic calibration of the basin model outputs by defining data likelihood distributions to represent well data uncertainty. Rock physics modeling transforms the basin modeling outputs to give us multiple velocity realizations used to perform multiple depth migrations. We have developed an approximate Bayesian inference framework that uses migration velocity analysis in conjunction with well data for updating velocity and basin modeling uncertainty. We apply our methodology in 2D to a real field case from the Gulf of Mexico; our methodology allows for building a geologic and physical model space for velocity and pore-pressure prediction with reduced uncertainty.
- Geology > Sedimentary Basin (1.00)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock (0.46)
- Geophysics > Seismic Surveying > Seismic Processing > Seismic Migration (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling (1.00)
ABSTRACT We show how vertical downhole distributed acoustic sensing arrays can be used for P- and S- velocity analysis along the array. Using such velocity models, the array can be used in an effective moveout-based earthquake detection approach. We demonstrate both applications on 20 days of passive records at the San Andreas Fault Observatory at Depth, which comprises of a ~800 m deep vertical array. Estimated P velocities are comparable to an active geophone survey and S velocities are extracted for the first time in the area. Over 75% of the events in the USGS catalog in the area are detected, as well as a new earthquake. Presentation Date: Tuesday, September 17, 2019 Session Start Time: 1:50 PM Presentation Time: 3:55 PM Location: 221C Presentation Type: Oral
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling (1.00)
- Geophysics > Seismic Surveying > Passive Seismic Surveying (1.00)
- Geophysics > Seismic Surveying > Seismic Processing (0.98)