Testing of the harmonic inversion method on the territory of the eastern part of Slovakia.

Slides:



Advertisements
Similar presentations
The general equation for gravity anomaly is: where:  is the gravitational constant  is the density contrast r is the distance to the observation point.
Advertisements

Gravitational Attractions of Small Bodies. Calculating the gravitational attraction of an arbitrary body Given an elementary body with mass m i at position.
§ 8.3 Quadratic Functions and Their Graphs.
§ 8.3 Quadratic Functions and Their Graphs. Graphing Quadratic Functions Blitzer, Intermediate Algebra, 5e – Slide #2 Section 8.3 The graph of any quadratic.
4. FREQUENCY DISTRIBUTION
The structure and evolution of stars
By S Ziaei-Rad Mechanical Engineering Department, IUT.
1.2 Row Reduction and Echelon Forms
Linear Equations in Linear Algebra
Chapter 3 Steady-State Conduction Multiple Dimensions
Caracas, Marzo 2006 Algorithm for 3D-Modeling H.-J. Götze IfG, Christian-Albrechts-Universität Kiel Interpretation Interpretation.
16 MULTIPLE INTEGRALS.
MULTIPLE INTEGRALS Double Integrals over General Regions MULTIPLE INTEGRALS In this section, we will learn: How to use double integrals to.
Gravity: Gravity anomalies. Earth gravitational field. Isostasy. Moment density dipole. Practical issues.
MOHAMMAD IMRAN DEPARTMENT OF APPLIED SCIENCES JAHANGIRABAD EDUCATIONAL GROUP OF INSTITUTES.
Grade 8 – Module 5 Module Focus Session
Chapter 7 Kinetic energy and work Key contents Work and kinetic energy Work done by gravity, springs and a variable force Power.
Gravitational Potential energy Mr. Burns
Introduction Information in science, business, and mathematics is often organized into rows and columns to form rectangular arrays called “matrices” (plural.
Copyright © Cengage Learning. All rights reserved. 1 Functions and Limits.
Copyright © Cengage Learning. All rights reserved. CHAPTER 11 ANALYSIS OF ALGORITHM EFFICIENCY ANALYSIS OF ALGORITHM EFFICIENCY.
Real Numbers and Their Properties รายวิชา ค ความรู้พื้นฐานสำหรับแคลคูลัส 1 ภาคเรียนที่ 1 ปีการศึกษา 2552.
Shape Blending Joshua Filliater December 15, 2000.
Gravity I: Gravity anomalies. Earth gravitational field. Isostasy.
ORDINARY DIFFERENTIAL EQUATION (ODE) LAPLACE TRANSFORM.
Chapter 6 The Normal Probability Distribution
Multiple Integrals 12. Double Integrals over General Regions 12.3.
Copyright © Cengage Learning. All rights reserved Double Integrals over General Regions.
DOUBLE INTEGRALS OVER GENERAL REGIONS
Gioko, A. (2007). Eds AHL Topic 9.3 Electric Field, potential and Energy.
§ 8.3 Quadratic Functions and Their Graphs. Blitzer, Intermediate Algebra, 4e – Slide #48 Graphing Quadratic Functions Graphs of Quadratic Functions The.
Worked examples and exercises are in the text STROUD (Prog. 28 in 7 th Ed) PROGRAMME 27 STATISTICS.
Testing of two variants of the harmonic inversion method on the territory of the eastern part of Slovakia.
1 Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Chapter 6. Continuous Random Variables Reminder: Continuous random variable.
A PPLIED M ECHANICS Lecture 09 Slovak University of Technology Faculty of Material Science and Technology in Trnava.
HSC Space: Section 1. Weight Whenever a mass is located within a gravitational field it experiences a force. It is that force, due to gravity, that.
P.1 Real Numbers. 2 What You Should Learn Represent and classify real numbers. Order real numbers and use inequalities. Find the absolute values of real.
1 Chapter 2: Motion along a Straight Line. 2 Displacement, Time, Velocity.
Copyright © Cengage Learning. All rights reserved.
Application of the two-step method for the solution of the inverse gravity problem for the Kolárovo anomaly.
Worked examples and exercises are in the text STROUD PROGRAMME 27 STATISTICS.
1 Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Chapter 6 Continuous Random Variables.
SECTION 12.5 TRIPLE INTEGRALS.
Copyright © Cengage Learning. All rights reserved.
Objectives Describe the purpose of the scientific method. Distinguish between qualitative and quantitative observations. Describe the differences between.
V.M. Sliusar, V.I. Zhdanov Astronomical Observatory, Taras Shevchenko National University of Kyiv Observatorna str., 3, Kiev Ukraine
Electromagnetism Topic 11.1 Electrostatic Potential.
Topics 1 Specific topics to be covered are: Discrete-time signals Z-transforms Sampling and reconstruction Aliasing and anti-aliasing filters Sampled-data.
1 1.2 Linear Equations in Linear Algebra Row Reduction and Echelon Forms © 2016 Pearson Education, Ltd.
CORRELATION-REGULATION ANALYSIS Томский политехнический университет.
Copyright © Cengage Learning. All rights reserved. 1 Functions and Limits.
CPH Dr. Charnigo Chap. 11 Notes Figure 11.2 provides a diagram which shows, at a glance, what a neural network does. Inputs X 1, X 2,.., X P are.
1 Variational and Weighted Residual Methods. 2 Introduction The Finite Element method can be used to solve various problems, including: Steady-state field.
Class 3 Linear System Solution Using the Laplace Transform
Gravity Data Reduction
Graphing Linear Equations and Inequalities
Copyright © Cengage Learning. All rights reserved.
Gravity II: Gravity anomaly due to a simple-shape buried body
Copyright © Cengage Learning. All rights reserved.
Copyright © Cengage Learning. All rights reserved.
Introduction Because we have already studied linear and quadratic functions, we can now begin working with exponential functions. In this lesson, we.
Algorithm An algorithm is a finite set of steps required to solve a problem. An algorithm must have following properties: Input: An algorithm must have.
Copyright © Cengage Learning. All rights reserved.
STATICS (ENGINEERING MECHANICS-I)
Copyright © Cengage Learning. All rights reserved.
Linear Equations in Linear Algebra
ENGINEERING MECHANICS
CONTINUOUS RANDOM VARIABLES AND THE NORMAL DISTRIBUTION
Linear Equations in Linear Algebra
Presentation transcript:

Testing of the harmonic inversion method on the territory of the eastern part of Slovakia

An improved version of the harmonic inversion method was tested on the territory of the eastern part of Slovakia. The improvement with respect to the initial version consists in the possibility to calculate position and shape of many anomalous bodies at once. The calculation is performed in two steps: first, from the surface gravitational field the characteristic density is obtained; second, the germs of anomalous bodies are placed in the local extrema of characteristic density and subsequently the true shapes of these bodies are determined iteratively. The evolution of the shapes of the anomalous bodies from the original germs to their final form was shown to be steady. The results of calculation are presented in numerous figures. Abstract

This version of harmonic inversion method is suitable for the case of planar Earth surface. This means that it was not accounted for: 1. the ellipsoidal shape of the Earth; 2. the topography. In order to avoid the problem in the point 2, the original gravimetric data were continued downwards to the zero height above the sea level by the method of Xia J., Sprowl D.R., 1991: Correction of topographic distortion in gravity data, Geophysics, 56, Introduction

Inverse gravimetric problem Density Surface gravitation Input: Output: (1)

Harmonic inversion method The inverse problem of gravimetry has infinitely many solutions. In order to obtain a reasonable solution(s), the following strategy was proposed: 1. to find the simplest possible solution; 2. to find some realistic solution(s). The simplest solution is defined as the maximally smooth density generating the given surface gravitation and having the extrema-conserving property; this density is a linear functional of the surface gravitation. The realistic solution is defined as a partially constant density; in other words, the calculation domain is divided in several subdomains and in each of these subdomains the density is a constant.

The simplest solution described above is called the characteristic density (of the given surface gravitation); thus it satisfies the following conditions: for the smallest possible 2. It is a linear integral transformation of the surface gravitation: 3. For the gravitational field of a point source, it has its main extremum at the point source. Characteristic density 1. It is the maximally smooth density generating the given surface gravitation:

(2) Formula for the characteristic density These conditions define uniquely the characteristic density; it will be denoted. In the condition 1 we have, thus the characteristic density is a tetraharmonic function. Formula for this density from the condition 2 reads Details can be found in: Pohánka V., 2001: Application of the harmonic inversion method to the Kolárovo gravity anomaly, Contr. Geophys. Inst. SAS, 31,

Input data Input was represented by points (coordinates x, y, gravitation a). The data were interpolated and extrapolated into a regular net of points in the rectangle 300 × 240 km with the step 0.5 km and the centre at 48º49'20" N, 21º16'20" E (totally points). The calculation domain was chosen as the rectangular prism whose upper boundary was the rectangle 200 × 140 km with the same centre as above and whose lower boundary was at the depth 50 km; the step in the depth was again 0.5 km (totally 401 × 281 × 100 = points ).

Characteristic density is a smooth function and thus it is not a realistic solution of the inverse problem. Characteristic density contains the same amount of information as the surface gravitation, but in another form: the information about the distribution of the sources of gravitational field with depth is hidden in the 2-dimensional surface gravitation, but it is restored in the 3-dimensional characteristic density. The extrema-conserving property of the characteristic density implies that for each domain where this density is positive (negative), there has to exist an anomalous body with positive (negative) difference density located roughly in this domain. This shows that the characteristic density is an important tool for finding the realistic solutions of the inverse problem. Significance of the characteristic density

Multi-domain density The realistic solution of the inverse problem can be represented by a multi- domain density; this is the density that is constant in each of the domains into which the halfspace is divided. For any multi-domain density, we calculate the surface gravitation generated by this density and then the corresponding characteristic density. Finally, we calculate the residual surface gravitation and the residual characteristic density. This quantity is identically zero if the density is a solution of the inverse problem.

Determination of the realistic solution If the residual characteristic density corresponding to the chosen multi-domain density is nonzero, the latter density has to be changed. This is done by changing the boundaries of the domains; the values of density in these domains remain unchanged. The changing of boundaries of particular domains is performed as follows: The whole calculation domain is divided into elementary cubic cells; each of these cells has its value of density. The cell is called a boundary cell just if at least one of the neighbouring cells has a different value of density; the other cells are called the interior ones. For each boundary cell, if the residual characteristic density in its centre is positive (negative), the value of density of this cell is changed to the nearest higher (lower) value from among its neighbours (if such neighbour exists). The result of these changes is the new multi-domain density.

Zero model The surface gravitation generated by any infinite horizontal layer with constant density is a constant function. The characteristic density corresponding to the constant surface gravitation is identically zero. This means that the infinite horizontal layers with constant density cannot be found if the only input is the surface gravitation. Therefore, the number and parameters of these layers have to be known in advance. The multi-domain density representing the layered calculation domain is called the zero model. The zero model serves as a reference model for any other models: The calculation of surface gravitation generated by any multi-domain density has to use the difference density, which is equal to the difference of the actual density and the value of the density of the zero model corresponding to the same depth.

Starting model The calculation of shapes of individual domains of the multi-domain density according to the above description has to start from some simple multi-domain density; the latter is called the starting model. The starting model is created from the zero model by changing the value of density in some number of individual cells; these cells are called the germs (of the future domains to be created from these cells in the calculation process). For any local extremum of the original characteristic density, a single germ is created at the same position as this extremum. The density value of each germ is a free parameter and has to be entered; for the positive (negative) value of the extremum, the density of the germ has to be greater (lower) than the density of the zero model at this depth. The suitable value of the difference density of the germ is of the order of the value of the characteristic density of this germ.

Calculation The calculation domain was divided into 401 × 281 × 100 = cells. The layers of the zero model were defined as follows: for the depth km the density is 2680 kg / m³, km 2700 kg / m³, km 2720 kg / m³, km 2740 kg / m³, km 2760 kg / m³, km 2780 kg / m³, km 3000 kg / m³, > 32 km 3300 kg / m³. The starting model had 1492 germs of anomalous bodies with densities in the range 2140 – 3300 kg / m³.

zero model

starting model

iteration 72

iteration 128

iteration 146

iteration 165

iteration 184

iteration 203

iteration 221

iteration 238

iteration 256

iteration 268

iteration 296

iteration 320

iteration 335

iteration 352

iteration 376

iteration 384

Results The calculations were performed on the Origin 2000 supercomputer of the Computing Centre of the Slovak Academy of Sciences. The calculation of the characteristic density took 2.08 hours of CPU time. The calculation of the resulting multi-domain density consisted of 384 iteration steps and it took hours of CPU time.