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https://github.com/OPM/ResInsight.git
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180 lines
6.6 KiB
C++
180 lines
6.6 KiB
C++
/////////////////////////////////////////////////////////////////////////////////
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//
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// Copyright (C) 2019- Equinor ASA
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//
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// ResInsight is free software: you can redistribute it and/or modify
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// it under the terms of the GNU General Public License as published by
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// the Free Software Foundation, either version 3 of the License, or
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// (at your option) any later version.
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//
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// ResInsight is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or
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// FITNESS FOR A PARTICULAR PURPOSE.
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//
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// See the GNU General Public License at <http://www.gnu.org/licenses/gpl.html>
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// for more details.
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//
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/////////////////////////////////////////////////////////////////////////////////
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#include "gtest/gtest.h"
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#include "Well/RigWellPathGeometryTools.h"
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#include <algorithm>
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#include <complex>
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#include <vector>
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#define TOLERANCE 1.0e-7
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#define SOLVER_TOLERANCE
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//--------------------------------------------------------------------------------------------------
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///
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//--------------------------------------------------------------------------------------------------
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TEST( RigWellPathGeometryTools, VerticalPath )
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{
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std::vector<double> mdValues = { 100, 500, 1000 };
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std::vector<double> tvdValues = { 100, 500, 1000 };
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std::vector<double> fullTVDValues = { 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000 };
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std::vector<double> fullMDValues = RigWellPathGeometryTools::interpolateMdFromTvd( mdValues, tvdValues, fullTVDValues );
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EXPECT_EQ( fullTVDValues.size(), fullMDValues.size() );
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for ( size_t i = 0; i < fullTVDValues.size(); ++i )
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{
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EXPECT_NEAR( fullTVDValues[i], fullMDValues[i], TOLERANCE );
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}
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}
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TEST( RigWellPathGeometryTools, LinearPath )
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{
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std::vector<double> mdValues = { 100, 500, 1000 };
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std::vector<double> tvdValues = { 50, 250, 500 };
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std::vector<double> fullTVDValues = { 50, 100, 150, 200, 250, 300, 350, 400, 450, 500 };
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std::vector<double> fullMDValues = RigWellPathGeometryTools::interpolateMdFromTvd( mdValues, tvdValues, fullTVDValues );
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EXPECT_EQ( fullTVDValues.size(), fullMDValues.size() );
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for ( size_t i = 0; i < fullTVDValues.size(); ++i )
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{
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EXPECT_NEAR( 2.0 * fullTVDValues[i], fullMDValues[i], TOLERANCE );
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}
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}
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TEST( RigWellPathGeometryTools, LinearPathStartingAtZero )
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{
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std::vector<double> mdValues = { 0, 100, 500, 1000 };
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std::vector<double> tvdValues = { 0, 50, 250, 500 };
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std::vector<double> fullTVDValues = { 0, 50, 100, 150, 200, 250, 300, 350, 400, 450, 500 };
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std::vector<double> fullMDValues = RigWellPathGeometryTools::interpolateMdFromTvd( mdValues, tvdValues, fullTVDValues );
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EXPECT_EQ( fullTVDValues.size(), fullMDValues.size() );
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for ( size_t i = 0; i < fullTVDValues.size(); ++i )
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{
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EXPECT_NEAR( 2.0 * fullTVDValues[i], fullMDValues[i], TOLERANCE );
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}
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}
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TEST( RigWellPathGeometryTools, ShortLinearPathStartingAtZero )
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{
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std::vector<double> mdValues = { 0, 1000.0 };
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std::vector<double> tvdValues = { 2000.0, 4000 };
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std::vector<double> fullTVDValues = { 0, 2000.0, 3000, 4000.0 };
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std::vector<double> expectedMDValues = { 0.0, 0.0, 500, 1000.0 };
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std::vector<double> fullMDValues = RigWellPathGeometryTools::interpolateMdFromTvd( mdValues, tvdValues, fullTVDValues );
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EXPECT_EQ( fullTVDValues.size(), fullMDValues.size() );
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for ( size_t i = 0; i < fullTVDValues.size(); ++i )
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{
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EXPECT_NEAR( expectedMDValues[i], fullMDValues[i], TOLERANCE );
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}
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}
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double quadraticFunction( double x )
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{
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return 0.0015 * std::pow( x, 2 ) - 0.25 * x + 100;
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}
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TEST( RigWellPathGeometryTools, QuadraticPath )
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{
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std::vector<double> mdValues = { 100, 300, 600, 1000 };
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std::vector<double> tvdValues;
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for ( double md : mdValues )
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{
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tvdValues.push_back( quadraticFunction( md ) );
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}
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std::vector<double> fullMDValues = { 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000 };
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std::vector<double> fullTvdValues;
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for ( double md : fullMDValues )
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{
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fullTvdValues.push_back( quadraticFunction( md ) );
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}
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std::vector<double> estimatedFullMDValues = RigWellPathGeometryTools::interpolateMdFromTvd( mdValues, tvdValues, fullTvdValues );
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EXPECT_EQ( estimatedFullMDValues.size(), fullMDValues.size() );
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for ( size_t i = 0; i < estimatedFullMDValues.size(); ++i )
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{
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if ( std::find( mdValues.begin(), mdValues.end(), estimatedFullMDValues[i] ) != mdValues.end() )
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{
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EXPECT_NEAR( fullMDValues[i], estimatedFullMDValues[i], TOLERANCE );
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}
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}
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}
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double cubicFunction( double x )
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{
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return 0.000012 * std::pow( x, 3 ) - 0.0175 * std::pow( x, 2 ) + 7 * x;
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}
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TEST( RigWellPathGeometryTools, CubicPath )
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{
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std::vector<double> mdValues = { 100, 300, 700, 1000 };
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std::vector<double> tvdValues;
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for ( double md : mdValues )
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{
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tvdValues.push_back( cubicFunction( md ) );
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}
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std::vector<double> fullMDValues = { 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000 };
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std::vector<double> fullTvdValues;
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for ( double md : fullMDValues )
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{
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fullTvdValues.push_back( cubicFunction( md ) );
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}
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std::vector<double> estimatedFullMDValues = RigWellPathGeometryTools::interpolateMdFromTvd( mdValues, tvdValues, fullTvdValues );
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EXPECT_EQ( estimatedFullMDValues.size(), fullMDValues.size() );
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for ( size_t i = 0; i < estimatedFullMDValues.size(); ++i )
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{
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if ( std::find( mdValues.begin(), mdValues.end(), estimatedFullMDValues[i] ) != mdValues.end() )
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{
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EXPECT_NEAR( fullMDValues[i], estimatedFullMDValues[i], TOLERANCE );
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}
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}
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}
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TEST( RigWellPathGeometryTools, CubicPathPoorSampling )
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{
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std::vector<double> mdValues = { 100, 300, 600, 1000 };
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std::vector<double> tvdValues;
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for ( double md : mdValues )
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{
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tvdValues.push_back( cubicFunction( md ) );
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}
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std::vector<double> fullMDValues = { 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000 };
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std::vector<double> fullTvdValues;
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for ( double md : fullMDValues )
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{
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fullTvdValues.push_back( cubicFunction( md ) );
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}
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std::vector<double> estimatedFullMDValues = RigWellPathGeometryTools::interpolateMdFromTvd( mdValues, tvdValues, fullTvdValues );
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EXPECT_EQ( estimatedFullMDValues.size(), fullMDValues.size() );
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for ( size_t i = 0; i < estimatedFullMDValues.size(); ++i )
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{
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if ( std::find( mdValues.begin(), mdValues.end(), estimatedFullMDValues[i] ) != mdValues.end() )
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{
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EXPECT_NEAR( fullMDValues[i], estimatedFullMDValues[i], TOLERANCE );
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}
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}
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}
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