diff --git a/Include/nmNum/nmCalculation/nmCalculationAutoFitPSO.h b/Include/nmNum/nmCalculation/nmCalculationAutoFitPSO.h
index 749aa99..2b1ccfb 100644
--- a/Include/nmNum/nmCalculation/nmCalculationAutoFitPSO.h
+++ b/Include/nmNum/nmCalculation/nmCalculationAutoFitPSO.h
@@ -340,7 +340,6 @@ private:
 	int m_localOptimumWindow;                // 局部最优观察窗口
 
 	// 质量评估参数
-	double m_nearTargetFactor;               // 接近目标的倍数因子
 	double m_farTargetFactor;                // 远离目标的倍数因子
 
 	// DLL求解器需要的临时目录。每个对象单独创建，析构或停止时递归清理。
diff --git a/Src/nmNum/nmCalculation/nmCalculationAutoFitPSO.cpp b/Src/nmNum/nmCalculation/nmCalculationAutoFitPSO.cpp
index f775bda..af09bd3 100644
--- a/Src/nmNum/nmCalculation/nmCalculationAutoFitPSO.cpp
+++ b/Src/nmNum/nmCalculation/nmCalculationAutoFitPSO.cpp
@@ -367,7 +367,6 @@ nmCalculationAutoFitPSO::nmCalculationAutoFitPSO(QObject* parent)
     , m_velocityConvergenceThreshold(0.01)
     , m_trueConvergenceWindow(15)
     , m_localOptimumWindow(8)
-    , m_nearTargetFactor(2.0)
     , m_farTargetFactor(10.0)
     , m_targetWellName("")
     , m_traceEnabled(true)
@@ -5166,17 +5165,14 @@ StopReasonPSO nmCalculationAutoFitPSO::analyzeOptimizationStatus()
 
 bool nmCalculationAutoFitPSO::checkTrueConvergence() const
 {
-    // 真收敛判断：不是只看“最近没有改进”，而是同时看解质量、误差稳定性、
-    // 粒子群多样性、平均速度、长期改进和粒子停滞率。
+    // 真收敛判断：不是只看“最近没有改进”，而是同时看误差稳定性、粒子群多样性、
+    // 平均速度、长期改进和粒子停滞率。
     // 这样可以减少把局部卡住误判成正常收敛的概率。
     if(m_convergenceHistory.size() < m_trueConvergenceWindow) {
         return false;
     }
 
-    // 1. 检查解质量 - 如果已经接近目标，小改进可能是真收敛
-    bool nearTarget = (m_globalBestFitness < m_targetError * m_nearTargetFactor);
-
-    // 2. 检查适应度稳定性 - 长期小幅波动
+    // 1. 检查适应度稳定性 - 长期小幅波动
     double recentVariance = calculateFitnessVariance(10);
     double recentMean = 0.0;
     int windowSize = qMin(10, m_convergenceHistory.size());
@@ -5191,32 +5187,28 @@ bool nmCalculationAutoFitPSO::checkTrueConvergence() const
     double relativeVariance = recentVariance / qMax(1e-10, recentMean * recentMean);
     bool stableError = (relativeVariance < m_convergenceVarianceThreshold);
 
-    // 3. 检查粒子群多样性 - 应该收敛到同一区域
+    // 2. 检查粒子群多样性 - 应该收敛到同一区域
     double currentDiversity = calculateSwarmDiversity();
     bool lowDiversity = (currentDiversity < m_diversityThreshold);
 
-    // 4. 检查速度收敛 - 粒子应该几乎停止移动
+    // 3. 检查速度收敛 - 粒子应该几乎停止移动
     double avgVelocity = calculateAverageVelocity();
     bool velocityConverged = (avgVelocity < m_velocityConvergenceThreshold);
 
-    // 5. 检查长期改进趋势
+    // 4. 检查长期改进趋势
     double longTermImprovement = calculateLongTermImprovement(m_trueConvergenceWindow);
     bool minimalLongTermImprovement = (longTermImprovement < 1e-4); // 0.01%
 
-    // 6. 检查粒子停滞情况
+    // 5. 检查粒子停滞情况
     double stagnationRate = calculateParticleStagnationRate();
     bool mostParticlesConverged = (stagnationRate > 0.8); // 80%以上粒子收敛
 
     // 真收敛的判断条件
-    bool isConverged = nearTarget ||
-                       (stableError && lowDiversity && velocityConverged &&
-                        minimalLongTermImprovement && mostParticlesConverged);
+    bool isConverged = stableError && lowDiversity && velocityConverged &&
+                       minimalLongTermImprovement && mostParticlesConverged;
 
     if(isConverged) {
         DEBUG_OUT("=== TRUE CONVERGENCE ANALYSIS ===");
-        DEBUG_OUT(QString("nearTarget=%1 (error=%2, target*factor=%3)")
-                  .arg(nearTarget).arg(m_globalBestFitness, 0, 'e', 4)
-                  .arg(m_targetError * m_nearTargetFactor, 0, 'e', 4));
         DEBUG_OUT(QString("stableError=%1 (relativeVariance=%2)")
                   .arg(stableError).arg(relativeVariance, 0, 'e', 6));
         DEBUG_OUT(QString("lowDiversity=%1 (diversity=%2, threshold=%3)")
diff --git a/Src/nmNum/nmData/nmDataReservoir.cpp b/Src/nmNum/nmData/nmDataReservoir.cpp
index 0994a48..5443e4d 100644
--- a/Src/nmNum/nmData/nmDataReservoir.cpp
+++ b/Src/nmNum/nmData/nmDataReservoir.cpp
@@ -4,7 +4,7 @@
 nmDataReservoir::nmDataReservoir() {
     // 基础属性
 	m_initialPressure = nmDataAttribute("Initial Pressure",40.0, "MPa", UNIT_TYPE_PRESSURE, QStringList(), QStringList() << "psia" << "Pa" << "kPa" << "atm" << "bara" << "kg/cm^2" << "m" << "psig" << "bar" << "MPa" << "kPag");
-    m_permeability = nmDataAttribute("Permeability", 0.001, "Darcy", UNIT_TYPE_PERMEABILITY, QStringList(), QStringList() << "md" << "Darcy" << "m^2" << "cm^2" << "um^2");
+    m_permeability = nmDataAttribute("Permeability", 0.025, "Darcy", UNIT_TYPE_PERMEABILITY, QStringList(), QStringList() << "md" << "Darcy" << "m^2" << "cm^2" << "um^2");
     m_thickness = nmDataAttribute("Thickness", 10.0, "m", UNIT_TYPE_LENGTH, QStringList(), QStringList() << "ft" << "m" << "cm" << "mm" << "in" << "0.1 in" << "mile" << "km");
     m_porosity = nmDataAttribute("Porosity", 0.1, "", UNIT_TYPE_DIMENSIONLESS, QStringList(), QStringList());
     m_kxKy = nmDataAttribute("Kx/Ky", 1.0, "", UNIT_TYPE_DIMENSIONLESS, QStringList(), QStringList());