تخمین تخلخل در یک مخزن هیدروکربوری با استفاده از ترکیب الگوریتم شبیه ساز تبرید و شبکه عصبی مصنوعی- مطالعه موردی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 عضو هیئت علمی دانشگاه صنعتی اراک

2 دانشگاه صنعتی اراک

چکیده

نخلخل یکی از خصوصیات اصلی ذخایر هیدروکربوری است که نشان دهنده حجم سیال منفذی و قابلیت حرکت کردن آن است. تعیین تخلخل توسط روش‌هایی مانند آنالیز مغزه مستلزم صرف زمان و هزینه گزافی می‌باشد و همچنین به علت نبود مغزه‌های کافی و تغییرات سنگ‌شناسی و ناهمگنی سنگ مخزن،‌ تعیین این پارامتر توسط روش‌های معمول از دقت چندانی برخوردار نمی‌باشد. روش‌های هوش محاسباتی از روش‌های جدید، کم هزینه و دقیقی هستند که می‌توانند با استفاده از داده‌‌های چاه‌نگاری، تخلخل مخزن را در کمترین زمان ممکن بصورت غیرمستقیم تخمین بزنند. لذا در این مطالعه با استفاده از چاه نگارهای مختلف و یک روش ترکیبی هوش محاسباتی (شبکه عصبی مصنوعی بهینه شده با الگوریتم شبیه‌ساز تبرید) تخلخل را در یکی از مخازن هیدروکربوری جنوب غربی ایران (میدان مارون) بصورت غیرمستقیم تخمین زده شده است. جهت بکارگیری این روش ترکیبی هوش محاسباتی پایگاه داده متشکل از 1356 داده‌ی چاه‌نگاری، شامل وزن مخصوص، تخلخل نوترون، لاگ مقاومت ویژه الکترومغناطیسی، لاگ پرتو گاما و لاگ صوتی می‌باشد. نتایج مدلسازی این تحقیق نشان می‌دهد که روش ترکیبی هوش محاسباتی مذکور برای تخمین غیر مستقیم تخلخل در مخازنی که تخلخل از طریق مغزه‌ اندازه‌گیری نشده دارای دقت و قابلیت بالایی است.

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