مانا بترو
SR-05متقدمةالموجة 3الذكاء الاصطناعي

النمذجة التوليدية بين الآبار

في جملة واحدة

Fills the rock between wells with geologically plausible detail instead of a smooth interpolation that no outcrop ever looked like.

المشكلة

Conventional geostatistics produces models that honour the wells and are far too smooth everywhere else. Flow behaviour is controlled by the connectivity of that in-between rock, which the smooth model gets wrong.

كيف تعمل

A generative model trained on analogue outcrop and high-resolution field datasets produces multiple realisations conditioned on well data and seismic attributes. Realisations are screened for geological plausibility by a geologist before any of them reach a simulator.

البيانات المطلوبة

  • Well data with facies and petrophysical curves
  • Seismic attributes or inversion volumes as soft conditioning
  • A depositional analogue set appropriate to the environment
  • Structural framework and zonation

ما الذي تحصل عليه

  • Multiple conditioned property realisations
  • Connectivity metrics across the realisation set
  • RESQML-ready grids for flow simulation

ما لا تستطيع فعله

Plausible is not correct. The realisations are consistent with the data and the analogue, and nothing in the method makes them true. They are useful for spanning uncertainty and dangerous if a single realisation is promoted to "the model", which is the most common way this technique is misused in the industry.

كل صفحة قدرة تذكر حداً حقيقياً. إن لم يستطع المورّد إخبارك أين يتوقف منتجه، فلم يُقل لك الحق عن أين يبدأ.

قدرات ذات صلة

  • SR-03متوسطة

    التصنيف الآلي للسحنات

    Labels rock type from well logs across hundreds of wells consistently, which a team of interpreters working separately cannot do.

    ذكاء تحت السطح والمكامنالذكاء الاصطناعي
  • SR-10متقدمة

    تحديد مواقع آبار التطوير

    Searches for where the next wells should go, with drilling feasibility and surface constraints inside the search rather than applied afterwards.

    ذكاء تحت السطح والمكامنالذكاء الاصطناعيالمجال