CAJ | 학술논문

人工神经网络近年来在石油行业中广泛使用,以稳定性和计算能力强为特点的BP神经网络更是广为应用.孔隙度和渗透率是储层物性的重要参数,在储层评价中占据重要地位.寻找一种广泛而有效的方法计算孔隙度和渗透率是石油工作者的一项艰巨任务,本文选用了BP神经网络分别建立计算孔隙度和渗透率的模型,并通过与岩芯分析数据作对比,取得了良好的效果,有进一步推广的潜力.
인공신경망락근년래재석유행업중엄범사용,이은정성화계산능력강위특점적BP신경망락경시엄위응용.공극도화삼투솔시저층물성적중요삼수,재저층평개중점거중요지위.심조일충엄범이유효적방법계산공극도화삼투솔시석유공작자적일항간거임무,본문선용료BP신경망락분별건립계산공극도화삼투솔적모형,병통과여암심분석수거작대비,취득료량호적효과,유진일보추엄적잠력.
Artificial neural network has been widely used in oil industry in recent years.Porosity and permeability are important parameters in reservoir evaluation.Looking for a broad and effective method to calculate the porosity and permeability is an arduous task of oil workers.In this paper,BP-ANN was used to establish the model which can be used to calculate porosity and permeability.It has been proved that the BP-ANN is effective and should be further promoted.