Cooperative inversion of geophysical data

Geophysics ◽  
1988 ◽  
Vol 53 (1) ◽  
pp. 8-20 ◽  
Author(s):  
Larry R. Lines ◽  
Alton K. Schultz ◽  
Sven Treitel
Keyword(s):  
Seismic Data ◽  
Field Model ◽  
Gravity Data ◽  
Geophysical Data ◽  
Rock Properties ◽  
Model Parameters ◽  
Borehole Data ◽  
Geophysical Inversion ◽  
Sonic Logs ◽  
Cooperative Inversion

Geophysical inversion by iterative modeling involves fitting observations by adjusting model parameters. Both seismic and potential‐field model responses can be influenced by the adjustment of the parameters of the rock properties. The objective of this “cooperative inversion” is to obtain a model which is consistent with all available surface and borehole geophysical data. Although inversion of geophysical data is generally non‐unique and ambiguous, we can lessen the ambiguities by inverting all available surface and borehole data. This paper illustrates this concept with a case history in which surface seismic data, sonic logs, surface gravity data, and borehole gravity meter (BHGM) data are adequately modeled by using least‐squares inversion and a series of forward modeling steps.

scholarly journals Disjoint interval bound constraints using the alternating direction method of multipliers (ADMM) for geologically constrained inversion: Application to gravity data

Geophysics ◽  
2020 ◽  
pp. 1-45
Author(s):  
Vitaliy Ogarko ◽  
Jérémie Giraud ◽  
Roland Martin ◽  
Mark Jessell
Keyword(s):  
Gravity Data ◽  
Alternating Direction Method ◽  
Rock Properties ◽  
Model Parameters ◽  
Method Of Multipliers ◽  
Geological Modeling ◽  
Bound Constraints ◽  
Data Inversion ◽  
Alternating Direction ◽  
Geological Information

To reduce uncertainties in reconstructed images, geological information must be introduced in a numerically robust and stable way during the geophysical data inversion procedure. In the context of potential (gravity) data inversion, it is important to bound the physical properties by providing probabilistic information on the number of lithologies and ranges of values of possibly existing related rock properties (densities). For this purpose, we introduce a generalization of bounding constraints for geophysical inversion based on the alternating direction method of multipliers (ADMM). The flexibility of the proposed technique enables us to take into account petrophysical information as well as probabilistic geological modeling, when it is available. The algorithm introduces a priori knowledge in terms of physically acceptable bounds of model parameters based on the nature of the modeled lithofacies in the region under study. Instead of introducing only one interval of geologically acceptable values for each parameter representing a set of rock properties, we define sets of disjoint intervals using the available geological information. Different sets of intervals are tested, such as quasi-discrete (or narrow) intervals as well as wider intervals provided by geological information obtained from probabilistic geological modeling. Narrower intervals can be used as soft constraints encouraging quasi-discrete inversions. The algorithm is first applied to a synthetic 2D case for proof-of-concept validation and then to the 3D inversion of gravity data collected in the Yerrida basin (Western Australia). Numerical convergence tests show the robustness and stability of the bound constraints we apply, which is not always trivial for constrained inversions. This technique can be a more reliable uncertainty reduction method as well as an alternative to other petrophysically or geologically constrained inversions based on more classical “clustering” or Gaussian-mixture approaches.

scholarly journals A fresh look at Gulf of Mexico tectonics: Testing rotations and breakup mechanisms from the perspective of seismically constrained potential-fields modeling and plate kinematics

2020 ◽  
Vol 8 (4) ◽  
pp. SS31-SS45
Author(s):  
Daniel Minguez ◽  
E. Gerald Hensel ◽  
Elizabeth A. E. Johnson
Keyword(s):  
Gulf Of Mexico ◽  
Seismic Data ◽  
Gravity Data ◽  
Seafloor Spreading ◽  
Plate Motion ◽  
Rock Properties ◽  
Satellite Gravity ◽  
Spreading Model ◽  
Breakup Mechanism ◽  
Mantle Exhumation

Interpretation of recent, high-quality seismic data in the Gulf of Mexico (GOM) has led to competing hypotheses regarding the basin’s rift to drift transition. Some studies suggest a fault-controlled mechanism that ultimately results in mantle exhumation prior to seafloor spreading. Others suggest voluminous magmatic intrusion accommodates the terminal extension phase and results in the extrusion of volcanic seaward dipping reflectors (SDRs). Whereas it has been generally accepted that the plate motions between the rift and drift phases of the GOM are nearly perpendicular to each other, it has not been greatly discussed if the breakup mechanism plays a role in accommodating the transition in plate motion. We have developed a plate kinematic and crustal architecture hypothesis to address the transition from rift to drift in the GOM. We support the proposition of a fault-controlled breakup mechanism, in which slip on a detachment between the crust and mantle may have exhumed the mantle. However, we stress that this mechanism is not exclusive of synrift magmatism, though it does imply that SDRs observed in the GOM are not in this case indicative of a volcanic massif separating attenuated continental and normal oceanic crust. We support our hypothesis through a geometrically realistic 2D potential field model, which includes a magnetic seafloor spreading model constrained by recent published seismic data and analog rock properties. The 2D model suggests that magnetic anomalies near the continent-ocean transition may be related to removal of the lower continental crust during a phase of hyperextension prior to breakup, ending in mantle exhumation. The kinematics of breakup, derived from recent satellite gravity data and constrained by our spreading model and the global plate circuit, suggests that this phase of hyperextension accommodated the change in plate motion direction and a diachronous breakup across the GOM.

The structure of the northeastern Gulf of St. Lawrence, Canada: new insight from geophysical data analysis

2001 ◽  
Vol 38 (11) ◽  
pp. 1495-1516 ◽  
Author(s):  
Nathan Hayward ◽  
Sonya A Dehler ◽  
Gordon N Oakey
Keyword(s):  
Seismic Data ◽  
Gravity Data ◽  
Complex Structure ◽  
Gravity Anomalies ◽  
Geological Structure ◽  
Geophysical Data ◽  
Normal Faults ◽  
Middle Ordovician ◽  
Clastic Rocks ◽  
Lower Amplitude

An improved compilation of magnetic and gravity data has been interpreted in conjunction with seismic reflection profiles to provide new information about the complex structure of the northeastern Gulf of St. Lawrence, Atlantic Canada. This region was affected by plate divergence and convergence events during the Grenville and Appalachian orogenies and the opening of the Iapetus Ocean. The Anticosti Basin, which developed as a foreland basin over the margin of Laurentia, is filled with a thick succession of Cambrian to Silurian sedimentary strata. Most of the interpreted magnetic and gravity anomalies have sources within the basement rocks, which is interpreted as Grenville crust beneath much of the study area. A V-shaped zone of lower amplitude gravity and magnetic anomalies in the center of the region is associated with a slight thickening of Cambrian to Middle Ordovician sedimentary rocks over a downthrown block of anorthositic Grenville crust, with a locally lower density and magnetization. Extensional faults bordering the zone presently display 130–250 m of downthrow at basement depths, increasing to the southeast, but show no disruption of strata younger than Middle Ordovician. A magnetic low 200 km to the northeast is of similar geophysical character and is associated with a similar geological structure. Numerous NE-trending normal faults associated with segmentation of the Grenville basement are manifested in the magnetic and seismic data. Related anomaly sources are also present within the overlying Ordovician calcareous and clastic rocks that were deposited during extension associated with the onset of the Taconian orogeny. Other anomalies are associated with faulting and folding of shallower strata, and seismic data indicate that some of the NE-trending faults were reactivated as thrusts towards the close of the Taconian orogeny in the Late Ordovician. The geophysical data show no evidence of significant deformation north of the western margin of Newfoundland that would be associated with later compressive events of the Acadian orogeny.

Cooperative deep learning inversion of controlled-source electromagnetic data for salt delineation

Geophysics ◽  
2020 ◽  
Vol 85 (4) ◽  
pp. E121-E137 ◽  
Author(s):  
Seokmin Oh ◽  
Kyubo Noh ◽  
Soon Jee Seol ◽  
Joongmoo Byun
Keyword(s):  
Deep Learning ◽  
Test Data ◽  
Seismic Data ◽  
Surrounding Medium ◽  
Geophysical Data ◽  
Single Type ◽  
Inversion Method ◽  
Data Types ◽  
Controlled Source ◽  
Cooperative Inversion

Various geophysical data types have advantages for exploring the subsurface, and more reliable exploration can be realized through integration of such data. However, the imaging of physical properties based on deep learning (DL) techniques, which has received considerable attention because of its enormous potential, has generally been performed using only a single type of data. We have developed a cooperative inversion method based on supervised DL for salt delineation. Controlled-source electromagnetic (CSEM) data, which can effectively distinguish a salt body with high electrical resistivity from the surrounding medium, are used as data for cooperative inversion, with high-resolution information derived from seismic data used as the constraint. This approach can entrain seismic information into a fully convolutional network designed to invert CSEM data to reconstruct the resistivity distribution. The inversion network is trained using large synthetic data sets, including the seismic information derived from seismic data as well as CSEM data and resistivity models. A cooperative strategy for reasonable entrainment of seismic information into the inversion network is established based on analysis of the network and kernels of the convolutional layers. The performance of the proposed method is demonstrated through experiments on test data generated for resistivity models for complex salt structures. The trained cooperative inversion network shows improved salt delineation results compared to the independent inversion network, irrespective of noise levels added to the test data, due to restriction of the resistivity model to fit seismic information. Moreover, training with noise-added data decreased the effects of noise on prediction results, similar to the case of adversarial training. We develop the possibility of combining geophysical data with a constraint using DL-based techniques.

Basin-wide empirical rock-physics transform and its application in Campeche Basin

2021 ◽  
Vol 40 (3) ◽  
pp. 178-185
Author(s):  
Yangjun (Kevin) Liu ◽  
Jonathan Hernandez Casado ◽  
Mohamed El-Toukhy ◽  
Shenghong Tai
Keyword(s):  
Pore Pressure ◽  
Wave Velocity ◽  
Effective Stress ◽  
Seismic Data ◽  
Sedimentary Basin ◽  
Rock Physics ◽  
P Wave ◽  
Rock Properties ◽  
Borehole Data ◽  
P Wave Velocity

Rock properties in the subsurface are of major importance for evaluating the petroleum prospectivity of a sedimentary basin. The key rock properties to understand are porosity, density, temperature, effective stress, and pore pressure. These rock properties can be obtained or calculated when borehole data are available. However, borehole data are usually sparse, especially in frontier basins. We propose some simple rock-physics transforms for converting P-wave velocity to other rock properties. We found that these rock-physics transforms are predictive in the east and west sides of Campeche Basin. The proposed rock-physics transforms can be used to obtain laterally varying rock properties based on information derived from seismic data.

Cooperative inversion of gravity and seismic data with different spatial coverage

2020 ◽  
Author(s):  
mahtab Rashidifard ◽  
Jérémie Giraud ◽  
Vitaliy Ogarko ◽  
Mark Lindsay ◽  
Mark Jessell
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Mineral Exploration ◽  
Gravity Data ◽  
Degree Of Freedom ◽  
Seismic Survey ◽  
Small Scale ◽  
Gravity Inversion ◽  
Spatial Coverage ◽  
Cooperative Inversion

<p>Combining two or more geophysical datasets with different resolutions and characteristics is now a common practice to recover one or more physical properties. Building 3D geological models for mineral exploration targeting is often an expensive task even for inversion of a single dataset, because of extremely complicated structures with small scale targets. In this context, seismic methods, among all other traditional techniques in mineral exploration, are receiving increasing attention due to their higher resolution in depth. With more limited spatial coverage and higher resolution, they are usually used to refine the interpretation of potential field data.</p><p>As each seismic survey is designed for a particular intention with specific targets and may not be available in all regions of interests, we develop an iterative cooperative inversion algorithm for inverting gravity and seismic travel-time data. This enables the utilization of localized high-resolution seismic data in a larger full 3D volume which is covered by gravity data. Geological information in the form of probabilistic geological modelling is used to extend information away from the high-resolution data and constrain the inversion result. We use these data as the prior model and to derive constraints incorporated into the objective function of gravity inversion. This allows us to obtain information about the probability of the presence of lithologies associated with the formation of mineral systems. To ensure structural consistency between density and velocity we develop a geologically constrained structure-based coupling technique following the same principle as the cross-gradient technique but with a higher degree of freedom in spatial directions. We apply local structure-based constraints conditioned by a geological probability distribution, which is considering direction and magnitude and provide a higher degree of freedom for model variations. An investigation of the proposed methodology and a proof-of-concept using realistic synthetic data are presented. Our results reveal that the methodology has the potential to constrain the gravity inversion results using the limited seismic data.</p>

Joint Gramian inversion of geophysical data with different resolution capabilities: case study in Yellowstone

2021 ◽  
Author(s):  
Xiaolei Tu ◽  
Michael S Zhdanov
Keyword(s):  
Joint Inversion ◽  
Gravity Data ◽  
Geophysical Methods ◽  
Structural Similarity ◽  
Geophysical Data ◽  
P Wave ◽  
Model Parameters ◽  
Magmatic System ◽  
Low Velocity ◽  
Velocity Anomaly

Summary Joint inversion of multiphysics data is a practical approach to the integration of geophysical data, which produces models of reduced uncertainty and improved resolution. The development of effective methods of joint inversion requires considering different resolutions of different geophysical methods. This paper presents a new framework of joint inversion of multiphysics data, which is based on a novel formulation of Gramian constraints and mitigates the difference in resolution capabilities of different geophysical methods. Our approach enforces structural similarity between different model parameters through minimizing a structural Gramian term, and it also balances the different resolutions of geophysical methods using a multiscale resampling strategy. The effectiveness of the proposed method is demonstrated by synthetic model study of joint inversion of the P-wave traveltime and gravity data. We apply a novel method based on Gramian constraints and multiscale resampling to jointly invert the gravity and seismic data collected in Yellowstone national Park to image the crustal magmatic system of the Yellowstone. Our results helped to produce a consistent image of the crustal magmatic system of the Yellowstone expressed both in low-density and low-velocity anomaly just beneath the Yellowstone caldera.

scholarly journals Model-Based Probabilistic Inversion Using Magnetic Data: A Case Study on the Kevitsa Deposit

Geosciences ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 150
Author(s):  
Nilgün Güdük ◽  
Miguel de la Varga ◽  
Janne Kaukolinna ◽  
Florian Wellmann
Keyword(s):  
Structural Parameters ◽  
Rock Properties ◽  
Magnetic Data ◽  
Geological Model ◽  
Borehole Data ◽  
Likelihood Functions ◽  
Different Types ◽  
Geophysical Information ◽  
Different Sources

Structural geological models are widely used to represent relevant geological interfaces and property distributions in the subsurface. Considering the inherent uncertainty of these models, the non-uniqueness of geophysical inverse problems, and the growing availability of data, there is a need for methods that integrate different types of data consistently and consider the uncertainties quantitatively. Probabilistic inference provides a suitable tool for this purpose. Using a Bayesian framework, geological modeling can be considered as an integral part of the inversion and thereby naturally constrain geophysical inversion procedures. This integration prevents geologically unrealistic results and provides the opportunity to include geological and geophysical information in the inversion. This information can be from different sources and is added to the framework through likelihood functions. We applied this methodology to the structurally complex Kevitsa deposit in Finland. We started with an interpretation-based 3D geological model and defined the uncertainties in our geological model through probability density functions. Airborne magnetic data and geological interpretations of borehole data were used to define geophysical and geological likelihoods, respectively. The geophysical data were linked to the uncertain structural parameters through the rock properties. The result of the inverse problem was an ensemble of realized models. These structural models and their uncertainties are visualized using information entropy, which allows for quantitative analysis. Our results show that with our methodology, we can use well-defined likelihood functions to add meaningful information to our initial model without requiring a computationally-heavy full grid inversion, discrepancies between model and data are spotted more easily, and the complementary strength of different types of data can be integrated into one framework.

scholarly journals Comparing global tomography-derived and gravity-based upper mantle density models

2020 ◽  
Vol 221 (3) ◽  
pp. 1542-1554 ◽  
Author(s):  
B C Root
Keyword(s):  
Seismic Tomography ◽  
Upper Mantle ◽  
Seismic Data ◽  
Gravity Data ◽  
Heterogeneous Data ◽  
Clear Correlation ◽  
Data Sets ◽  
Satellite Gravity ◽  
Similar Density ◽  
Similar Peak

SUMMARY Current seismic tomography models show a complex environment underneath the crust, corroborated by high-precision satellite gravity observations. Both data sets are used to independently explore the density structure of the upper mantle. However, combining these two data sets proves to be challenging. The gravity-data has an inherent insensitivity in the radial direction and seismic tomography has a heterogeneous data acquisition, resulting in smoothed tomography models with de-correlation between different models for the mid-to-small wavelength features. Therefore, this study aims to assess and quantify the effect of regularization on a seismic tomography model by exploiting the high lateral sensitivity of gravity data. Seismic tomography models, SL2013sv, SAVANI, SMEAN2 and S40RTS are compared to a gravity-based density model of the upper mantle. In order to obtain similar density solutions compared to the seismic-derived models, the gravity-based model needs to be smoothed with a Gaussian filter. Different smoothening characteristics are observed for the variety of seismic tomography models, relating to the regularization approach in the inversions. Various S40RTS models with similar seismic data but different regularization settings show that the smoothening effect is stronger with increasing regularization. The type of regularization has a dominant effect on the final tomography solution. To reduce the effect of regularization on the tomography models, an enhancement procedure is proposed. This enhancement should be performed within the spectral domain of the actual resolution of the seismic tomography model. The enhanced seismic tomography models show improved spatial correlation with each other and with the gravity-based model. The variation of the density anomalies have similar peak-to-peak magnitudes and clear correlation to geological structures. The resolvement of the spectral misalignment between tomographic models and gravity-based solutions is the first step in the improvement of multidata inversion studies of the upper mantle and benefit from the advantages in both data sets.

On the Processing of Non-Rectangularly Sampled Multi-Dimensional Geophysical Data

1991 ◽  
Vol 02 (01) ◽  
pp. 223-226
Author(s):  
VIRGIL BARDAN
Keyword(s):  
Seismic Data ◽  
Geophysical Data ◽  
Seismic Sections

In this paper the processing of triangularly sampled 2-D seismic data is illustrated by examples of synthetic and field seismic sections.

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