Constructing piecewise-constant models in multidimensional minimum-structure inversions

Geophysics ◽  
2008 ◽  
Vol 73 (1) ◽  
pp. K1-K9 ◽  
Author(s):  
Colin G. Farquharson
Keyword(s):  
Gravity Data ◽  
Model Structure ◽  
Iteratively Reweighted Least Squares ◽  
3D Inversion ◽  
Magnetotelluric Data ◽  
2D Inversion ◽  
Piecewise Constant ◽  
Text Type ◽  
Current Minimum ◽  
Modified Algorithm

A modification of the typical minimum-structure inver-sion algorithm is presented that generates blocky, piecewise-constant earth models. Such models are often more consistent with our real or perceived knowledge of the subsurface than the fuzzy, smeared-out models produced by current minimum-structure inversions. The modified algorithm uses [Formula: see text]-type measures in the measure of model structure instead of the traditional sum-of-squares, or [Formula: see text], measure. An iteratively reweighted least-squares procedure is used to deal with the nonlinearity introduced by the non-[Formula: see text] measure. Also, and of note here, diagonal finite differences are included in the measure of model structure. This enables dipping interfaces to be formed. The modified algorithm retains the benefits of the minimum-structure style of inversion — namely, reliability, robustness, and minimal artifacts in the constructed model. Two examples are given: the 2D inversion of synthetic magnetotelluric data and the 3D inversion of gravity data from the Ovoid deposit, Voisey’s Bay, Labrador.

scholarly journals Geothermal Reservoir Identification in Way Ratai Area Based on Gravity Data Analysis

2021 ◽  
Vol 2110 (1) ◽  
pp. 012004
Author(s):  
M Sarkowi ◽  
R C Wibowo ◽  
Karyanto
Keyword(s):  
Density Distribution ◽  
Gravity Data ◽  
Bouguer Anomaly ◽  
Geothermal Reservoir ◽  
Gravity Gradient ◽  
Low Density ◽  
3D Inversion ◽  
Magnetotelluric Data ◽  
Fault Structure ◽  
Geothermal Reservoirs

Abstract Gravity research in the Way Ratai geothermal prospect area was conducted to determine geothermal reservoirs, heat sources, and the structure of the geothermal reservoir. The research carried out includes 3D inversion modeling of gravity data. The Bouguer anomaly in the study area has 50 mGal to 120 mGal with low anomalies located in the southeast (Ketang and Kelagian), Northeast (Gedong Air, Sungai Langka, Gunung Betung) areas, and in the Pesawaran mountain area. The high anomaly is in Merawan – Hanuberak – Padang Cermin, Sumbersari and Kaliawi. The horizontal gravity gradient map analysis shows a pattern of fault structure trending northwest-southeast and southwest-northeast, according to the main fault structure in the area. 3D inversion modeling obtains a density distribution between 1.8 g/cc to 3g/cc with a low-density distribution in the south, Mount Pesawaran/Ratai, Gunung Betung, and Sidoharum. The location of the manifestation is 9 km southeast of the Mount Ratai/Pesawaran summit. The existence of geothermal reservoirs is estimated to be in the Lubuk Badak and Miwung Hills areas which are located between the peaks of Mount Ratai/Pesawaran and geothermal manifestations. This is supported by the low-density distribution in the area and the resistivity map from audio-magnetotelluric data.

A Modified Algorithm for the Least Squares Identification

1983 ◽  
Vol 105 (1) ◽  
pp. 50-52
Author(s):  
C. Batur
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Mechanical Systems ◽  
Model Structure ◽  
Input Output ◽  
Unknown Parameters ◽  
Estimation Errors ◽  
Usual Practice ◽  
Unknown Disturbances ◽  
Modified Algorithm

To identify the dynamics of mechanical systems, the usual practice is to assume a certain model structure and try to estimate the unknown parameters of this model on the basis of input output observations. For mechanical systems operating under noisy industrial conditions, the number of unknowns of the problem exceeds the number of equations available. It is then inevitable that certain assumptions must be made on the unknown disturbances. This paper assumes that the only reliable feature of the disturbance is its independence of input. This yields a set of assumptions in excess of the minimal requirements and an endeavor has been made to exploit this excess to minimize the parameter estimation errors. Th resulting algorithm is similar to that of the Two Stage Least Squares method [1].

2D Inversion of Magnetotelluric Data over 3D Structures

1997 ◽  
Author(s):  
P. Pastana de Lugao ◽  
B. Krieghäuser
Keyword(s):  
Magnetotelluric Data ◽  
2D Inversion ◽  
3D Structures
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