The Simulation of Magnetic and Gravity Profiles by Digital Computer

Isaacs, Kalman N.

doi:10.1190/1.1439809

Cited by 3 publications

(1 citation statement)

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“…Two-di men sional (2-D) grav ity in ver sion has been used for many years to au to mat i cally in ter pret grav ity data (Corbato 1965;Bott 1967;Tan ner 1967;Negi and Garde 1969;Al-Chalabi 1972;Dyrelius and Vogel 1972;Pedersen 1975;Enmark 1981;García-Abdeslem 2003). In a con ventional ap proach, the for ward mod el ing is based on a set of 2-D prisms of ar bi trary shape (Talwani et al 1959;Isaacs 1966;Bhattacharyya and Navolio 1976;Mar tin-Atienza and García-Abdeslem 1999) and uses den sity con trast vary ing in depth. It works well for grav ity data col lected across a sed i men tary ba sin or an ore body.…”

Section: Introductionmentioning

confidence: 99%

A Study of Complex Substructures in a Foothill Belt of Northwestern Taiwan Using Two-Dimensional Gravity Multiple-Source Model Inversion

Yu¹,

Yang²,

Kang³

et al. 2009

Terr. Atmos. Ocean. Sci.

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The goal of this pa per is to im prove the ca pa bil ity of grav ity in ver sion as sess ment of com plex struc tures us ing a mul ti ple-source model as in di cated by a study of a foot hill belt of north west ern Tai wan. In this study, a grav ity in ver sion com puter pro gram is ap plied based on re search de vel oped by Tsai, which con tains a Marquardt in ver sion al go rithm for math e mat i cal cal cu la tions and in cor po rates con straints on geo log i cal pa ram e ters. The com puted and mod i fied geo log i cal pa ram e ters are trans formed into co or di nates. The re sponse of a proper geological model is calculated using the Talwani technique. The method is ap plied to a field ex am ple in a foot hills belt of Tai wan that pos sesses com plex subsurface struc tures. The den sity pro file from 2D grav ity data, ob tained us ing our in ver sion com puter pro gram, re veals a good cor re la tion with the geo log i cal model ob tained from seis mic, bore hole, and geo logic data. Fur ther more, po ten tial hy dro car bon traps as so ci ated with some of the in ter preted geo log i cal struc tures (where no seis mic data are avail able) in the east ern and west ern seis mic sec tions are be ing eval u ated and as sessed for pos si ble fu ture de vel op ment. This pro file high lights fea tures that are im por tant to a good un der stand ing of an area with com plex subsurface struc tures. It also helps to de fine subsurface ge ol ogy and as sess po ten tial hy dro car bon traps. This two-di men sional mul ti ple-source model grav ity in ver sion algorithm provides a powerful tool to interpret the gravity data in this study.

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Section: Introductionmentioning

confidence: 99%

A Study of Complex Substructures in a Foothill Belt of Northwestern Taiwan Using Two-Dimensional Gravity Multiple-Source Model Inversion

Yu¹,

Yang²,

Kang³

et al. 2009

Terr. Atmos. Ocean. Sci.

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Interpretation of Potential Field Data a Generalized Inverse Approach*

Pedersen

1977

Geophysical Prospecting

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The interpretation of potential field data from two‐dimensional structures with a single interface of density or susceptibility contrasts is solved in terms of generalized matrix inversion. The model equations are derived, and important features of generalized matrix inversion are treated. The method is subsequently used to solve two gravity problems, an artificial one where the solution is known, and a geophysical one related to the crust‐mantle interface. The solution is shown to compare well with the FFT results of Oldenburg. The method is also used to solve two magnetic problems, an artificial one with the solution known, and a geophysical one from the continental shelf of Greenland. The advantages and limitations of the method are finally discussed.

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A Quick Look Kriging Technique for Reservoir Characterisation

Brown

Falade

2003

All Days

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Correct descriptions of reservoir rock heterogeneity provide useful input for simulation models and are essential for efficient reservoir management. This paper discusses a novel kriging technique that uses sparse irregularly spaced permeability data to generate permeability values at other points within chosen grid blocks. A uniquely designed computer program, expressed in FORTRAN provides solution to the sequence of algorithms required for the solution of the kriging system in the absence of more sophisticated kriging models. Results obtained from the model allows for relatively cheap and reasonably accurate characterization of heterogeneous reservoirs. Introduction The processes of deposition, tectonism and environmental sequences occurring over millions of years are responsible for the heterogeneous nature of reservoir rocks. Optimum success in hydrocarbon recovery depends largely on adequate knowledge of the reservoir rock parameters. The task of quantifying the porous media heterogeneity, therefore, is the major challenge for the reservoir engineer. A common obstacle encountered by the reservoir engineer, especially at an early stage of field development, is almost always the lack of sufficient control data (from cores, logs, seismic, etc.) that is necessary to correctly predict the internal architecture of the reservoir and estimate its petrophysical properties. The use of oversimplified geologic models based on data from a limited number of widely spaced wells is probably one of the most important reasons for the failures in predicting field performance. Stochastic or geostatistical models are capable of expressing the nature of a property's variation and its disposition in a useful mathematical form and also of providing detailed distributions of physical properties. These distributions can honour the available data, some statistical functions (like the histogram) and the variogram of the reservoir. Probabilistic (geostatistical or stochastic) modeling is used to take advantage of this capacity and still quantify the uncertainty due to the lack of information. Stochastic techniques, therefore, seek to generate synthetic variability in a certain phenomenon or parameter which ‘fills in the gaps’ between observations and descriptive needs in terms of detail. Some geostatistical or stochastic techniques of estimation include Kriging, Co-Kriging, Conditional simulation, Fractal techniques and Transition probability (Markov) procedures. Any of these can be adopted as a model for characterising the spatial structure of property variations.

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The Simulation of Magnetic and Gravity Profiles by Digital Computer

Cited by 3 publications

References 0 publications

A Study of Complex Substructures in a Foothill Belt of Northwestern Taiwan Using Two-Dimensional Gravity Multiple-Source Model Inversion

A Study of Complex Substructures in a Foothill Belt of Northwestern Taiwan Using Two-Dimensional Gravity Multiple-Source Model Inversion

Interpretation of Potential Field Data a Generalized Inverse Approach*

A Quick Look Kriging Technique for Reservoir Characterisation

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