Unlock instant, AI-driven research and patent intelligence for your innovation.

Rock facies prediction in non-cored wells from cored wells

A technology of non-coring wells and coring wells, which is applied in measurement devices, data processing applications, geophysical measurements, etc., and can solve problems such as damage accuracy, long time, and consumption

Inactive Publication Date: 2015-08-19
SAUDI ARABIAN OIL CO
View PDF4 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This manual intervention and interpretation takes a very long time, often days or weeks
Accuracy is often compromised due to regional development time constraints, which exclude some wells and logs from the reservoir from the interpretation process

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Rock facies prediction in non-cored wells from cored wells
  • Rock facies prediction in non-cored wells from cored wells
  • Rock facies prediction in non-cored wells from cored wells

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0036]By means of the present invention, predictions or hypotheses are made about lithofacies in oil and gas reservoir drilling. A neural network-like network is used to construct training images from lithofacies, which are descriptions and interpretations of each rock face using existing data obtained from certain wells in the reservoir and well log parameters from those same wells. Well logs from wells drilled without well core data were then analyzed against the training images and assumptions were made about lithofacies in non-cored wells.

[0037] As will be presented, the present invention first incorporates lithofacies based on description and interpretation using well core data from wells drilled in the reservoir from which cores were taken. The well log parameters for these same wells were then reviewed for each rock face. The present invention uses data obtained by interpreting well core data as well as well log data from the same well to construct training images i...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

Facies in wells in areas of a hydrocarbon reservoir are predicted or postulated. Artificial neural networks are utilized to build a training image based on rock phases which are described and interpreted using existing data obtained from certain wells in the reservoir, and also well log characteristics of those same wells for each rock facies. Well logs from which wells where no well core data has been collected are then analyzed against the training image and the rock facies in the non-cored wells are postulated. The cost and also the possibility of damage to the wells from extraction of the core rock during drilling are avoided.

Description

[0001] Cross References to Related Applications [0002] This application claims priority to US Provisional Applications 61 / 719,594, filed October 29, 2012 and 13 / 888,013, filed May 6, 2013. technical field [0003] The present invention relates to computer simulations of the physical structure of lithofacies of subterranean oil and gas reservoirs, in particular based on neural network-like determinations using training images obtained from existing core samples and analysis of well logs from certain wells drilled in the reservoir lithofacies. Background technique [0004] Comprehensive oil and gas development planning relies on several kinds of data. Data can be categorized as soft data and hard data. Soft data includes seismic data acquired at the surface through reflections from the subsurface, which provide indirect measurements. Hard data, such as well core data, is based on observations of real rock extracted from boreholes thousands of feet deep. Well core data pr...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G01V11/00G01V99/00
CPCG01V11/00G01V99/005G01V20/00Y10S706/929E21B2200/22
Inventor 罗格·R·松Y·李C·斯蒂芬·孙
Owner SAUDI ARABIAN OIL CO