M5 Log Upscaling

August 2, 2017 | Author: Anonymous 4hvWNxu9V | Category: Arithmetic Mean, Logarithm, Median, Mathematics, Science
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M5 Log Upscaling...

Description

Module 5 Property Modeling

Petrel Workflow Tools Surfaces and Data edit

Stratigraphic Modeling

3D Grid Construction: Structural Modeling

Interface Studio

Pillar Gridding

Fault Modeling 3D Grid Construction Structural Framework

3D Grid Construction Structural Gridding

Property Modeling

Well Log Upscale

Facies & Petrophysical Modeling

Make Horizons Zones & Layering Make contacts & Volume Calculation Workflow Editor

Intro to Petrel

Introduction

Upscaling of Well Logs Objectives     

Gain an understanding of the concept and process Understand and use discrete logs – Averaging methods – Facies weighting. Understand and use continuous logs – Averaging methods – Biasing to a discrete log. Look at different Scale-up settings – Treat log as lines or points – Method of which penetrated cells to use. QC of upscaled logs: Using well section window.

Overview The Scale-up well logs process averages the values to the cells in the 3D grid that are penetrated by the wells. Each cell gets one value per upscaled log. These cells are later used as a starting point for Property modeling. Cells exist along the well path.

Values assigned to cells based on well log values along the well path.

Upscaled logs used to fill in the 3D grid.

Note: An upscaled property will have a [U] following its name in the Property folder in the Models pane.

Scale-Up Well Logs 1. Create a new property.

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2. Select Input from Well logs.

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3. Choose a log from the drop-down list (captured from Input pane > Global well logs folder) 4. Set the best scale-up Settings, depending on the type of log (continuous or discrete).

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5. Click Apply or OK.

Note: Upscaled logs will be part of the 3D property at the well positions. The Property modeling processes will NOT overwrite upscaled cell values!

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Commonly used Averaging Methods Averaging method

Description

Most of

Used together with discrete logs, it selects the discrete value that is most represented in the log for each particular cell.

Arithmetic mean

Typically used for additive properties, such as porosity, saturation, and net/gross.

Harmonic mean

Gives the effective vertical permeability if the reservoir is layered with constant permeability in each layer. It works well with lognormal distributions and is sensitive to lower values.

Geometric mean

Normally a good estimate for permeability if it has no spatial correlation and is lognormally distributed. It is sensitive to lower values.

Averaging Discrete Logs Discrete logs, such as facies, have only integer values (0,1,2, etc.). 1. Choose an input from a Facies well log to create a new property. 2. The Average method is normally Most of, which uses the value most represented in the cell.

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3. In some situations, it may be necessary to use the Weighting option. Click Use weighting and fill in the Weighted tab.

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Averaging Continuous Logs Continuous logs, such as porosity, have real number values (decimals). 1. Choose an input from a continuous Well log to create a new property (here, porosity). 2. Set the Average method (here Arithmetic for porosity).

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3. It is possible to bias to an already upscaled facies log.

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4. Specify that there should be a Minimum number of well log samples in a cell for it to be included in the upscaling.

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Biasing to a Discrete Log Raw porosity

Raw facies

Sand

Shale

Upscaled facies

Upscaled porosity

Settings: Treat Log as Lines or Points Treat log

Description

As points

All sample values within each cell are used for averaging.

As Lines

If the midpoint of a line between two sample points is inside a cell the point outside the cell will be used in the calculation.

Settings: Method of Which Penetrated Cells to Use Method

Description

Simple

All cells penetrated by the well trajectory are included.

Through cell

The well trajectory must penetrate two opposite cell walls.

Neighbor cell

All penetrated cells are used but cells in the same cell layer are averaged.

Quality Checking Upscaled Logs When upscaling is done, it is a good practice to QC the upscaled cells with the original log in a Well section window. 1. Click the Show result in well section button in the Scale up well logs dialog.

Alternatively, set up a Well section display on your own. Choose raw logs (Global well logs folder > Input pane), right-click, and select Add to template in a new track. 2. Display the upscaled log in the same track. Right-click on the upscaled log (Models pane> Properties folder) and click Add to template in the existing raw log track.

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Averaged values for each cell in the model on top of the original log

EXERCISE

Upscaling of Well Logs: QC of Upscaled Logs Synthetic logs resemble the properties (Upscaled logs) but are stored as physical logs under Global Well Logs. 1. Click the Make logs tab of settings for Wells. 2. Choose the property from which the log will be made. 3. Click the Make logs button. The log is stored in the Global Well Logs folder and can be toggled on from there.

Averaging Methods for Discrete Logs Averaging method

Description

Most of

Will select the discrete value which is most represented in the log for each particular cell

Median

Will sort the input values and select the center value.

Minimun/Maximum

Samples the min/max value of the well log for the cell.

Mid Point Pick

Will pick the log value where the well is halfway through the cell.

Random Pick

Picks a log point at random from anywhere within the cell.

Averaging Methods for Continuous Logs Averaging method

Description

Arithmetic mean

Typically used for additive properties such as porosity, saturation, and net/gross.

Harmonic mean

Gives the effective vertical permeability if the reservoir is layered with constant permeability in each layer. It works well with log normal distributions. It is sensitive to lower values.

Geometric mean

Normally a good estimate for permeability if it has no spatial correlation and the is log normally distributed. It is sensitive to lower values.

Median

Sorts the input values and select the center value.

RMS (Root Mean Squared)

Provides a strong bias towards high values.

Minimun/Maximum

Samples the min/max value of the well log for the cell.

Mid Point Pick

Picks the log value where the well is halfway through the cell.

Random Pick

Picks a log point at random from anywhere within the cell.

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