PREDICTION OF PERMEABILITY AT WELL LOG SCALE USING GAUSSIAN RANDOM FUNCTION SIMULATION AND MACHINE LEARNING
Permeability data is exclusively obtainable from laboratory testing conducted on core samples and well tests extracted from many wells. Frequently, this data is used to make inferences and estimate the permeability of the entire field. Nevertheless, the absence of sufficient data typically leads to...
Saved in:
Main Author: | Tangkin, Sukma |
---|---|
Format: | Theses |
Language: | Indonesia |
Subjects: | |
Online Access: | https://digilib.itb.ac.id/gdl/view/81863 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Similar Items
-
EXPLORING MACHINE LEARNING ALGORITHMS FOR PREDICTING POROSITY, PERMEABILITY, AND ROCK TYPE FROM WELL LOG DATA
by: Izzam Tursina, Afgha -
MACHINE LEARNING APPLICATION TO PREDICT POROSITY AND PERMEABILITY USING LOG & CORE MEASUREMENTS CASE STUDY FOR FIELD X
by: Fairuz Gibran, Ahnaf -
INTEGRATION OF CONVENTIONAL WELL LOGS AND MACHINE LEARNING APPROACHES FOR FRACTURE TYPE PREDICTION: A CASE STUDY ON VOLCANIC RESERVOIRS IN INDONESIA
by: Arifinka Alhazmi, Enricho -
INTEGRATED RESERVOIR CHARACTERIZATION FROM WELL LOG DATA USING MACHINE LEARNING ALGORITHMS
by: Benny Setyo Nugroho, Muhammad -
INTERPRETASI OTOMATIS DATA WELL LOG UNTUK EVALUASI IKATAN SEMEN: PENDEKATAN MACHINE LEARNING
by: Azmi, Muhammad