#11172: Move decline curve math to RigDeclineCurveCalculator

Add least squares regression as an alternative to the start/end point fit.

ApplicationLibCode/UnitTests/RigDeclineCurveCalculator-Test.cpp

@@ -20,6 +20,8 @@
 
 #include "RigDeclineCurveCalculator.h"
 
+#include <vector>
+
 // Test case from https://web.archive.org/web/20120710104333/http://infohost.nmt.edu/~petro/faculty/Kelly/Deline.pdf
 // Example Problem 8-1:
 // "Given that a well has declined from 100 stb/day to 96 stb/day during a one-month period,
@@ -55,3 +57,70 @@ TEST( RigDeclineCurveCalculatorTests, exponentialFlowRateExample )
 
     EXPECT_NEAR( q, 61.27, 0.005 );
 }
+
+//--------------------------------------------------------------------------------------------------
+///
+//--------------------------------------------------------------------------------------------------
+TEST( RigDeclineCurveCalculatorTests, fitRecoversParametersFromSyntheticData )
+{
+    const double qi = 100.0;
+    const double di = 0.4 / ( 365.25 * 24.0 * 3600.0 ); // per second
+    const double b  = 0.5;
+
+    std::vector<double> times;
+    std::vector<double> exponential, harmonic, hyperbolic;
+    for ( int i = -20; i <= 0; i++ )
+    {
+        const double t = i * 30.0 * 24.0 * 3600.0;
+        times.push_back( t );
+        exponential.push_back( RigDeclineCurveCalculator::computeFlowRateExponentialDecline( qi, di, t ) );
+        harmonic.push_back( RigDeclineCurveCalculator::computeFlowRateHarmonicDecline( qi, di, t ) );
+        hyperbolic.push_back( RigDeclineCurveCalculator::computeFlowRateHyperbolicDecline( qi, di, t, b ) );
+    }
+
+    auto expFit = RigDeclineCurveCalculator::fitExponentialDecline( times, exponential );
+    ASSERT_TRUE( expFit.has_value() );
+    EXPECT_NEAR( qi, expFit->first, 1.0e-6 );
+    EXPECT_NEAR( di, expFit->second, 1.0e-12 );
+
+    auto harmonicFit = RigDeclineCurveCalculator::fitHarmonicDecline( times, harmonic );
+    ASSERT_TRUE( harmonicFit.has_value() );
+    EXPECT_NEAR( qi, harmonicFit->first, 1.0e-6 );
+    EXPECT_NEAR( di, harmonicFit->second, 1.0e-12 );
+
+    auto hyperbolicFit = RigDeclineCurveCalculator::fitHyperbolicDecline( times, hyperbolic, b );
+    ASSERT_TRUE( hyperbolicFit.has_value() );
+    EXPECT_NEAR( qi, hyperbolicFit->first, 1.0e-6 );
+    EXPECT_NEAR( di, hyperbolicFit->second, 1.0e-12 );
+}
+
+//--------------------------------------------------------------------------------------------------
+///
+//--------------------------------------------------------------------------------------------------
+TEST( RigDeclineCurveCalculatorTests, fitFailsWithTooFewValidPoints )
+{
+    EXPECT_FALSE( RigDeclineCurveCalculator::fitExponentialDecline( { -10.0, 0.0 }, { 0.0, 5.0 } ).has_value() );
+}
+
+//--------------------------------------------------------------------------------------------------
+///
+//--------------------------------------------------------------------------------------------------
+TEST( RigDeclineCurveCalculatorTests, historyIsBackwardExtrapolationOfFittedCurve )
+{
+    const double day = 24.0 * 3600.0;
+
+    using Calc = RigDeclineCurveCalculator;
+    Calc::DeclineModel model{ Calc::DeclineCurveType::EXPONENTIAL, Calc::FitMethod::REGRESSION, 0.5, false };
+
+    // Noisy history around an exponential decline
+    std::vector<time_t> timeSteps = { 0, static_cast<time_t>( 100 * day ), static_cast<time_t>( 200 * day ), static_cast<time_t>( 300 * day ) };
+    std::vector<double> values = { 100.0, 80.0, 66.0, 50.0 };
+
+    auto result = Calc::computeDeclineCurveValues( model, values, timeSteps, { static_cast<time_t>( 400 * day ) } );
+    ASSERT_TRUE( result.has_value() );
+    ASSERT_EQ( 5u, result->size() );
+
+    EXPECT_NE( values[0], ( *result )[0] );
+    EXPECT_GT( ( *result )[0], ( *result )[1] );
+    EXPECT_GT( ( *result )[3], ( *result )[4] );
+}