Integration of seismic and gravity data — A case study from the western Gulf of Mexico

2015 ◽  
Vol 3 (4) ◽  
pp. SAC99-SAC106 ◽  
Author(s):  
Irina Filina ◽  
Nicholas Delebo ◽  
Gopal Mohapatra ◽  
Clayton Coble ◽  
Gary Harris ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Gravity Field ◽  
Gravity Model ◽  
Seismic Velocity ◽  
Gravity Data ◽  
Public Domain ◽  
Gravity Modeling ◽  
Data Sets ◽  
Gardner Equation ◽  
Well Data

A 3D gravity model was developed in the western Gulf of Mexico in the East Breaks and Alaminos Canyon protraction areas. This model integrated 3D seismic, gravity, and well data; it was constructed in support of a proprietary seismic reprocessing project and was updated iteratively with seismic. The gravity model was built from seismic horizons of the bathymetry, salt layers, and the acoustic basement; however, the latter was only possible to map in seismic data during the latest iterations. In addition, a deep layer representing the Moho boundary was derived from gravity and constrained by public-domain refraction data. A 3D density distribution was derived from the seismic velocity volume using a modified Gardner equation. The modification comprised imposing a depth dependency on the Gardner coefficient, which is constant in the classic Gardner equation. The modified coefficient was derived from well data in the study area and public-domain velocity-density data sets. The forward-calculated gravity response of the composed density model was then compared with the observed gravity field, and the mismatch was analyzed jointly by a seismic interpreter and a gravity modeler. Adjustments were then made to the gravity model to ensure that the resultant salt model was geologically reasonable and supported by gravity, seismic, and well data sets. The output of the gravity modeling was subsequently applied to the next phase of seismic processing. Overall, this integration resulted in a more robust salt model, which has led to significant improvements in subsalt seismic imaging. The analysis of the regional trend in the observed gravity field suggested that a stretched continental crust underlay our seismic reprocessing area, with an oceanic-continental transition zone located to the southeast of our reprocessing region.

Kinematic linkage between minibasin welds and extreme overpressure in the deepwater Gulf of Mexico

2014 ◽  
Vol 2 (1) ◽  
pp. SB69-SB77 ◽  
Author(s):  
Niven Shumaker ◽  
Daniel Haymond ◽  
Joe Martin
Keyword(s):  
Gulf Of Mexico ◽  
Seismic Velocity ◽  
Large Degree ◽  
Data Sets ◽  
Seismic Velocities ◽  
Burial History ◽  
Well Control ◽  
Deep Blue ◽  
Exploration Well ◽  
Primary Section

A geopressure interpretation technique known as the seismic velocity method is a common workflow in which shale compaction functions are characterized at offset control wells, matched to interval seismic velocities, and then used to predictively calculate geopressure away from well control. The seismic velocity method is used to interpret the expected geopressure profile at the Deep Blue subsalt exploration well in Green Canyon 723 in the deep water Gulf of Mexico. The Deep Blue prospect is distinct from other prospects in the play fairway in that the prospective section is overlain by a salt withdrawal minibasin, whereas the offsetting fields are positioned either along the flanks of minibasins or under a thick allochthonous salt canopy. Predrill geopressure interpretations using numerous tomographic imaging velocity data sets shows a large degree of consistency with the magnitude of geopressure encountered in offsetting supra salt and subsalt fields. Results from the Deep Blue 1 exploration well indicate the predrill geopressure interpretation from interval seismic velocities failed to anticipate the extreme degree overpressure encountered in the subsalt section of the well due to poor deep velocity resolution and an “unloaded” compaction signature. The magnitude of overpressure in the primary section is attributed to the emplacement of an unconformable halokinetic sequence over the primary subsalt basin. An interpretive paradigm is described in which the Deep Blue pressure cell is created through two halokinetic episodes: (1) rapid progradation of a salt canopy followed by (2) subsequent salt withdrawal and emplacement of an overlying minibasin. The linkage between halokinetic sequences, burial history, and the development of overpressure can be used to predictively characterize subsalt geopressure environments.

scholarly journals The scaling behaviour of the edges of gravity data

2013 ◽  
Vol 20 (3) ◽  
pp. 287-291
Author(s):  
G. R. J. Cooper
Keyword(s):  
South Africa ◽  
Gravity Field ◽  
Gravity Model ◽  
Gravity Data ◽  
Statistical Distribution ◽  
Earth’S Gravity Field ◽  
Geological Interpretation ◽  
Geophysical Exploration ◽  
Scaling Behaviour ◽  
Interpretation Process

Abstract. Measurements of the earth's gravity field are widely used in geophysical exploration programs. The geological interpretation process often involves the identification of the boundaries, or edges, of different regions. This can be achieved through a variety of techniques. This paper examines the statistical distribution of the size of the edges produced by a synthetic gravity model, and compares the results with those obtained from a gravity dataset from South Africa.

scholarly journals Multiphysics data modeling and imaging for exploration in the southern Rocky Mountains

2018 ◽  
Vol 6 (3) ◽  
pp. SG59-SG78 ◽  
Author(s):  
Maria Soledad Velasco ◽  
David Alumbaugh ◽  
Emmanuel Schnetzler
Keyword(s):  
Cross Sections ◽  
Predictive Analytics ◽  
Gravity Data ◽  
Volcanic Rocks ◽  
Data Sets ◽  
Mathematical Framework ◽  
Magnetotelluric Data ◽  
Land Access ◽  
Southern Rocky Mountains ◽  
Well Data

We carried out a multidata geophysics study in southern Colorado to explore for [Formula: see text] reservoirs in an area where seismic imaging is very limited due to the mountainous terrain, the presence of high-velocity volcanic rocks, and difficulty in obtaining land access permits. We have developed a modeling/interpretation methodology using ground magnetotelluric data as well as airborne magnetic and electromagnetic data combined with public domain gravity data and existing well and seismic data. We used the integration of these data sets to produce a series of 2D and 3D geophysical models that reveal basin architecture previously poorly defined through the analysis of limited seismic and well data alone. We found that this type of analysis aids in decreasing uncertainty in the interpreted geologic cross sections and a better understanding of the structural complexities of the region. Through the application of machine learning methods, we are also able to integrate several data sets into a mathematical framework resulting in a predictive model of spatial [Formula: see text] distribution. The integration of the interpretations from all data sets, predictive analytics results, and knowledge of [Formula: see text] production, allows us to delineate areas of interest for further exploration.

Coupling USArray and satellite gravity data – an integrated conductivity, density and seismic velocity model of the western USA

2020 ◽  
Author(s):  
Bernhard Weise ◽  
Max Moorkamp ◽  
Stewart Fishwick
Keyword(s):  
Seismic Velocity ◽  
Joint Inversion ◽  
Gravity Data ◽  
Velocity Model ◽  
Data Sets ◽  
Satellite Gravity ◽  
Consistent Model ◽  
The Usa ◽  
The Individual ◽  
Tectonic Boundaries

<p>The EarthScope USArray project provides high quality magnetotelluric and seismic observations, which have been used to identify tectonic boundaries of the USA. Combining these data sets together with satellite gravity observations, we investigate how the different data sets can complement each other in order to find a consistent model of the subsurface. Using a cross-gradient constraint, we first invert the magnetotelluric and gravity data sets in order to demonstrate the feasibility of our approach and to identify any difficulties. Once a joint conductivity and density model is found, we perform a full joint inversion of all three data sets. By comparison with models derived from separate inversions of the individual observables we can show how the different data sets interact. Examining the magnitude of the cross-gradient lets us distinguish parts of the model where a good agreement of the recovered structures has been achieved from those where differing patterns are necessary in order to achieve an acceptable data fit. In this presentation we will give an overview of our approach, highlight our strategy and show results from individual and joint inversions.</p>

2-D inversion of gravity data using sources laterally bounded by continuous surfaces and depth‐dependent density

Geophysics ◽  
2000 ◽  
Vol 65 (4) ◽  
pp. 1128-1141 ◽  
Author(s):  
Juan García‐Abdeslem
Keyword(s):  
Sensitivity Analysis ◽  
Gravity Data ◽  
Synthetic Data ◽  
Gravity Modeling ◽  
Inversion Method ◽  
Data Sets ◽  
Nonlinear Inversion ◽  
Correlation Matrices ◽  
Significant Difference ◽  
Dependent Density

A description is given of numerical methods for 2-D gravity modeling and nonlinear inversion. The forward model solution is suitable for calculating the gravity anomaly caused by a 2-D source body with depth‐dependent density that is laterally bounded by continuous surfaces and can easily accommodate different kinds of geologic structures. The weighted and damped discrete nonlinear inverse method addressed here can invert both density and geometry of the source body. Both modeling and inversion methods are illustrated with several examples using synthetic and two field gravity data sets—one over a sulfide ore body and other across a sedimentary basin. A sensitivity analysis is carried out for the resulting solutions by means of the resolution, covariance, and correlation matrices, providing insight into the capabilities and limitations of the inversion method. The inversion of synthetic data provides meaningful results, showing that the method is robust in the presence of noise. Its sensitivity analysis indicates an almost perfect resolution and small covariance, but high correlation between some parameters. Differences in the asperity aspect of the inverted‐field data sets turned out to be important for the inversion capabilities of the algorithm, making a significant difference in the resolution achieved, its covariance, and the degree of correlation among parameters.

Gravity model of the Aulneau batholith, northwestern Ontario

1980 ◽  
Vol 17 (8) ◽  
pp. 968-977 ◽  
Author(s):  
W. C. Brisbin ◽  
A. G. Green
Keyword(s):  
Gravity Field ◽  
Gravity Model ◽  
Surface Density ◽  
Gravity Data ◽  
Three Dimensional ◽  
Gravity Survey ◽  
Northwestern Ontario

A gravity survey over the Aulneau batholith, northwestern Ontario, shows that the batholith is expressed as a gravity low of approximately 40 mGal relative to the level of the gravity field over neighbouring greenstone rocks. Assuming that surface density contrasts extend to depth, then three-dimensional modelling of the gravity data indicates that the floor of the batholith, in general, is located between depths of 4.5–7 km. Locally, in two regions, prominent plugs extend to 11–12 km depth. The modelling also suggests that the wall contacts of the batholith are generally steep and inward dipping, a picture supported by earlier seismic studies.

scholarly journals Forty-three years of absolute gravity observations of the Fennoscandian postglacial rebound in Finland

2021 ◽  
Vol 95 (2) ◽  
Author(s):  
Mirjam Bilker-Koivula ◽  
Jaakko Mäkinen ◽  
Hannu Ruotsalainen ◽  
Jyri Näränen ◽  
Timo Saari
Keyword(s):  
Gravity Data ◽  
Gravity Change ◽  
Global Navigation Satellite Systems ◽  
Absolute Gravity ◽  
Data Sets ◽  
Postglacial Rebound ◽  
Land Uplift ◽  
Satellite Systems ◽  
Gravity Measurements ◽  
Global Navigation Satellite

AbstractPostglacial rebound in Fennoscandia causes striking trends in gravity measurements of the area. We present time series of absolute gravity data collected between 1976 and 2019 on 12 stations in Finland with different types of instruments. First, we determine the trends at each station and analyse the effect of the instrument types. We estimate, for example, an offset of 6.8 μgal for the JILAg-5 instrument with respect to the FG5-type instruments. Applying the offsets in the trend analysis strengthens the trends being in good agreement with the NKG2016LU_gdot model of gravity change. Trends of seven stations were found robust and were used to analyse the stabilization of the trends in time and to determine the relationship between gravity change rates and land uplift rates as measured with global navigation satellite systems (GNSS) as well as from the NKG2016LU_abs land uplift model. Trends calculated from combined and offset-corrected measurements of JILAg-5- and FG5-type instruments stabilized in 15 to 20 years and at some stations even faster. The trends of FG5-type instrument data alone stabilized generally within 10 years. The ratio between gravity change rates and vertical rates from different data sets yields values between − 0.206 ± 0.017 and − 0.227 ± 0.024 µGal/mm and axis intercept values between 0.248 ± 0.089 and 0.335 ± 0.136 µGal/yr. These values are larger than previous estimates for Fennoscandia.

scholarly journals Unbiased least-squares modification of Stokes’ formula

2020 ◽  
Vol 94 (9) ◽  
Author(s):  
Lars E. Sjöberg
Keyword(s):  
Gravity Data ◽  
Harmonic Series ◽  
Local Error ◽  
Data Sets ◽  
Spherical Cap ◽  
Local Variance ◽  
Error Covariance ◽  
Stokes Formula ◽  
Gravity Signal ◽  
High Degree

Abstract As the KTH method for geoid determination by combining Stokes integration of gravity data in a spherical cap around the computation point and a series of spherical harmonics suffers from a bias due to truncation of the data sets, this method is based on minimizing the global mean square error (MSE) of the estimator. However, if the harmonic series is increased to a sufficiently high degree, the truncation error can be considered as negligible, and the optimization based on the local variance of the geoid estimator makes fair sense. Such unbiased types of estimators, derived in this article, have the advantage to the MSE solutions not to rely on the imperfectly known gravity signal degree variances, but only the local error covariance matrices of the observables come to play. Obviously, the geoid solution defined by the local least variance is generally superior to the solution based on the global MSE. It is also shown, at least theoretically, that the unbiased geoid solutions based on the KTH method and remove–compute–restore technique with modification of Stokes formula are the same.

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.

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