The fitness values during the MABC optimization.

<div><p>Porosity is a key parameter for evaluating reservoir performance, but high-precision prediction is highly challenging in complex shale reservoirs due to the strong heterogeneity of the formation and the highly nonlinear relationship between logging parameters and porosity. Tradit...

وصف كامل

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Wei Su (89824) (author)
مؤلفون آخرون:	Jie Gao (10266) (author), Wensheng Wu (703888) (author), Haoyu Zhang (1783690) (author)
منشور في:	2025
الموضوعات:	Molecular Biology Ecology Cancer Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified performing reservoir evaluations low generalization ability gamma ray log evaluating reservoir performance best predictive performance physical models often highly nonlinear relationship true porosity curve intelligent optimization algorithm lssvm model exhibits div >< p optimization algorithm comparison models optimization model highly consistent highly challenging study proposes strong heterogeneity significantly higher section index results show r </ proposed model prediction results precision prediction porosity prediction pe ), lssvm model key parameter inertia weights hybrid model gbdt ), gas exploration findings demonstrate driven methods determination (< complex formations acceleration coefficients >< sup
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

The fitness values during the MABC optimization.

مواد مشابهة