OilField Manager
Forecast Analysis
Fundamentals
Training and Exercise Guide
Version 2005.1
Schlumberger Information Solutions
May 16, 2005
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Creating a Forecast Analysis
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Table of Contents
Chapter 1
Creating Forecast Analysis ............................................................ 2
Learning Objectives ............................................................................................................ 2
Setting Up a Forecast Scenario ......................................................................................... 3
Editing the Graph ................................................................................................................ 7
Working with Different Forecasting Features................................................................... 14
Hyperbolic Fit Type ................................................................................................... 17
Exponential Fit Type.................................................................................................. 23
Add Schedule ............................................................................................................ 25
Exponential Fit Type.................................................................................................. 27
Manual Match for Empirical Solutions.............................................................................. 41
Chapter 2
Forecast.......................................................................................... 44
Using the Output Features ............................................................................................... 44
Working with Cases .......................................................................................................... 47
Auto Decline...................................................................................................................... 49
Chapter 3
Additional Forecasts ..................................................................... 51
Water Cut versus Cum.Oil Analysis ................................................................................. 51
P/Z vs. Cum.Gas Analysis................................................................................................ 55
Chapter 4
Fetkovich Type Curve Analysis ................................................... 64
Using Fetkovich Type Curve Analysis (Late-Time) ......................................................... 65
Chapter 5
Analytical Transient Solutions..................................................... 75
Using Analytical Transient Solutions................................................................................ 75
Chapter 6
Retrieving Forecast Results......................................................... 85
Calculated Variables ......................................................................................................... 85
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Chapter 1
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Creating Forecast Analysis
Welcome to Introduction to Forecast Analysis in OilField Manager (OFM)!
In this course you will learn how to use empirical and analytical techniques to
forecast production and retrieve forecast information for further studies.
Formerly known as Decline Curve Analysis (DCA), the Forecast module in
OFM has been enhanced to facilitate more sophisticated analyses. In OFM
2005, the Forecast module consists of four major categories (techniques);
Empirical, Fetkovich, Locke & Sawyer, and Analytical Transient solutions.
Forecasts can be done on single well (completion) level, category level, or on
a group of wells. If you choose to perform the forecast on a group of wells, the
forecast result will be slightly different than that of grouped individual well
forecasts (i.e. summing the individual forecasts). This is the issue of “forecast
of a group” vs. “group of the forecasts”.
Interactive manual match techniques for empirical solutions are introduced in
this version of OFM. OFM will initially plot control points based on historical or
digitized data regression. Once a control point is moved, manual match
method is automatically activated and the user will have total control of how
the match should be performed.
The Well Deliverability Analysis enables you to analyze data from FlowAfter-Flow tests (Back Pressure Analyses), Isochronal Tests, and Modified
Isochronal Tests using the following empirical equation, q=C(Pws^2 - Pwf ^2)
^n.
The online Help file has been updated for the Forecast module. All the terms
used in this module have been documented to give users more
comprehensive information.
Learning Objectives
In this section, you will be introduced to the fundamentals of creating forecast
analysis. You will successfully learn how to perform the following procedures
within this workflow:
•
Set up a forecast scenario
•
Use different forecast features
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In addition to basic forecasts like rate vs. time, rate vs. cum, OFM allows you
to perform more advanced techniques such as ratios and cuts vs. cum.
Fetkovich, Locke & Sawyer and Analytical Transient Solution techniques
are type-curve analyses, which require better understanding of the reservoir
model as well as the parameters controlling the well/entity behavior. In this
lesson, you will focus on using the Empirical method of forecasting. There is a
session covering the basics of Fetkovich and Analytical Transient methods.
More in-depth coverage of the type curve-based methods will be addressed in
more advanced OFM training courses.
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Setting Up a Forecast Scenario
In the Demo2005 database, about half of the wells are not productive and
approximately 80% of the other half has already stopped producing. We are
going to use the active producer after 1998.
1. From the Filter pane, select the Well List node, right-click and select
Open. The Well List dialog displays.
2. Select Prod_Wells98.txt and click Open.
Note: If you do not have the well list or the query file, please take some time to
set up the query to do it. The definition of the query is (Monthlyprod.Oil > 50) &
(Date >= 19980101), the criteria is met 3 times, and the Consecutively box
checked. It should resemble the image below.
3. Click OK to save the query.
4. From the Filter pane, select the newly created filter to apply the conditions
to the basemap.
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5. Click
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to Group all the wells.
6. Select Analysis>Forecast. The forecast tabbed page is displayed in the
OFM main window.
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7. Select Edit>Scenario Manager. The Scenario Manager dialog displays.
8. Highlight the DefaultScenario from the Scenarios list and click Edit. The
Edit Scenario dialog displays.
9. Select Oil from the Phase/Analysis list field.
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10. For this phase (Oil), the Time (Date) variable should be Date.
11. The Cum.Oil variable should be Oil.Cum (a monthly frequency variable);
the Oil Rate variable is Oil.CalDay.
12. Go through all other phases (Gas and Water) and Ratios (GOR, WOR,
Water Cut, and Oil Cut) and set them up accordingly. Reselect the Oil
phase.
13. Select the Historical Regression tab. We will work on the Oil phase and
use the Empirical method.
14. Select Best Method from the Method section of the dialog.
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15. Select the Forecast tab.
16. You are defaulted to Schedule 1. In that schedule, specify the following:
Start Time – Months from End, starting at 0 (zero) month
•
Start Rate – Last Historical Rate
•
Reserve Type – Proven-Developed
•
End Time – Months from Start, set for 60 months (5 years)
•
End Rate. Enter 1 as the end limit.
•
Decline Type – Historical Regression
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Note: The Forecast tab has lots of options. Please read the online help to
understand the usage of those available options (for example, when to use
Last Historical Rate, and when to use From Historical).
17. Click OK.
Editing the Graph
1. Now that the forecast scenario is set, it is time to work on the appearance
of the graph. Select Edit>Graph or right-click on the graph and select the
Graph option from the menu. The Edit Plot dialog in Forecast module is
similar to the Edit Plot dialog in Plot module.
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Notes:
Database Forecast - Once you like your forecast result, you can save
it to the database. This database forecast result can be retrieved from
other modules in this project.
•
Working Forecast - Forecasting is an ongoing process. As long as
you have not saved your forecast result yet, your forecast is still a
“working forecast”. Working forecast results can only be seen in the
Forecast module, not anywhere else in the project.
•
Control Points - In this module, you can select to exclude data points
(that you do not think are reliable), so they do not affect your result.
Working points then have different attributes to distinguish with
excluded points. Control Points are the end and middle points used for
the manual match.
•
Fitted Curve - Attributes of the fitted line.
•
Historical - Attributes of the diagnostic variable data (historical data).
2. Locate the Legend section of the Properties pane.
3. Click in the field to the right of Result Items. This action enables a browse
button.
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4. Click the button to display the Result Legend Items dialog and select the
result items to display.
5. Clear the checkbox of the parameters you do not want to display and click
OK.
6. Locate the Graph Settings section of the Properties pane.
7. Click in the field to the right of Setup. This action enables a browse button.
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8. Click this button to open the Headers dialog.
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9. Click Add.
10. Click Assist and enter "Forecast: "+@name().
11. Click OK.
12. Add another header that reports today’s date. The definition is @fmtdate(
@today(), "mm/dd/yyyy"). Your Headers dialog should resemble the
image pictured below.
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13. Click OK. The graph displays. Move and edit the Header/Label Fonts,
resize the graph, move the legend to get an output similar to the one
pictured below.
Notes:
•
To move a header, use the left mouse button in a “drag and drop”
operation.
•
To edit the headers, select Edit>Graph>Headers.
•
To move/resize graph, click the right mouse on the graph and select
Graph Move/Size.
•
To move Legend and/or Axis Label, use the left mouse button to “drag
and drop”, or highlight the item to move then select Move from the
right mouse click menu.
•
The Legend/Axis Label Fonts can be edited from the right mouse
click>Font menu. The Label can also be modified via from the right
mouse click>Edit menu.
14. Select Edit>Limits>Lower.
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15. Click to draw the line under the last declining portion of the historical curve
as shown.
16. When the action is complete, right-click and select Done from the shortcut
menu.
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Notes:
•
When applying the Lower Limit line, any data points below and out of
the line are excluded.
•
When drawing the line, the right mouse click gives you the options to
complete or undo (last or all) the operation.
17. Select File>Case (or click the Save button), to save to the current case,
Case1.
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Note: (Optional) You can save to another case using Save to Different Case
by select File>Save to Different Case.
You can edit the group name now for future use if you wish.
If you do not suppress warning messages, OFM will provide a message to
remind you that you have to regroup before the saved forecasts can be
viewed in other modules.
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Working with Different Forecasting Features
1. Locate the Step toolbar at the top of the OFM main window.
2. Click
Next. The BLUE_1:Ge_6 well displays.
3. Place a lower limit on the data as shown to exclude the first and the last
two data points. Right-click and select Done when finished.
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Our starting rate is set at Last Historical Rate, which may not be very good
with insufficient historical data and with the last historical rate excluded.
4. Select Edit>Scenario, click the Forecast tab and select Last Fit Rate
from the Start Rate list.
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5. Click OK. Save the forecast (from File>Save or using the Save button) and
the graph displays.
6. Click Next. The forecast for BLUE_1:He_0 displays (based on the default
case).
Note: that the best-fit case for historical regression is Exponential. However,
excluding the first few data points that are not representative of the well’s
decline behavior, the best fit should be hyperbolic.
7. Place the lower limit as shown. Right-click and select Done.
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Note: The start time is at the last date of the project. In this case, we may want
to start forecasting from the last historical date of the well.
8. Select Edit>Scenario.
9. Select the Forecast tab, and select Last Historical Date from the Start
Time list.
10. Click OK. Save the forecast. The graph displays.
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11. Click Next. The working forecast for BLUE_5:Sc_0 displays.
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Even though it appears to be a good fit, and the forecast looks acceptable,
there are things that we can do to obtain a better result.
12. Place a lower limit (and upper limit if needed) to rule out the anomalous
data points (noise), for example at the beginning of the production history.
Hyperbolic Fit Type
1. Locate the Historical Match section of the Properties pane.
2. Set the Fit Type to Hyperbolic.
3. Set the b Value Method to User.
4. Set the User value to 0.6 (if you do not enter your own b-value, OFM will
select the best b-value to use Hyperbolic regression).
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5. Select Edit>Scenario and click on the Forecast tab.
6. From the Start Rate list, select From Fit.
Note: In the Decline Parameters Type list box, the Historical Regression
option is selected. It means that the forecast will be the continuation of the
historical hyperbolic regression. You can also select the Hyperbolic in the
Decline Type list box, and then enter the value of 0.6 for the “b-value”. The
result should be similar if you enter a value for decline rate that is close to the
default (calculated) decline case.
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7. Click OK.
8. Click Next. The forecast for GREEN_4:Ad_3BU displays.
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Note that the last historical rate is already below the economic limit. Thus there
is no default forecast on this well. Still we can reasonably perform the forecast
on this well.
9. Place a lower limit as shown in the image below.
10. Select Edit>Scenario.
11. Select the Forecast tab.
12. Select Last Historical Date for Start Time.
13. Select From Fit for Start Rate.
14. From the Decline Parameters Type list field select Exponential.
15. From the Decline Parameters Rate list field select User Defined and
enter 0.01 for Decline Rate.
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16. Click OK.
17. Click Next. The forecast for GREEN_6:Li_1C displays.
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18. Place an upper limit as shown in the image below.
19. From the Properties pane, modify the following settings from the History
Match section.
20. Set the Fit Type value to Hyperbolic.
21. Set the b Value Method to Range.
22. Set the Minimum and Maximum values to 0.3 and 0.6, respectively.
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23. Click Next. The forecast for ORANGE_18:De_3 displays.
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24. Place a lower limit as shown in the image below.
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25. Place an upper limit as shown in the image below.
Exponential Fit Type
1. From the Properties pane change the Fit Type to Exponential.
2. Select Edit>Scenarios.
3. Select the Forecast tab.
4. Select Last Historical Date for Start Time.
5. Select Last Fit Rate for Start Rate.
6. Click OK.
7. Save the forecast.
8. Click Next. The forecast for ORANGE_19:Ad_1A displays.
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This well has a good history of production. As seen, the decline trend from
1984 to 1994 could be identified as the common trend of the well. Somewhere
in 1996, a work over was successfully completed with significant increase in
production afterwards. The decline trend after work over has been different
from the common trend. Further studies of this completion indicate that the
well would follow this current trend for a short period and then return to the
historical best-fit trend. This will be a case to apply a multiple schedule
forecast.
9. Set the lower limit as shown in the image below.
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10. Set the upper limit to exclude the points that constitute the spike in late
1995, early 1996.
11. Select Edit>Scenario.
12. Select the Forecast tab.
13. Specify the following:
•
Start Time - Months from End. Enter “0” in the adjoining field.
•
Start Rate - Last Historical Rate.
•
End Time - Months from Start. Enter “30” (months) in the adjoining
field.
•
End Rate - 1.
•
Decline Parameter Type - Exponential.
•
Rate - User Defined and 0.03 in the adjoining field.
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Add Schedule
1. Click Add to add Schedule #2.
2. Specify the following:
•
Start Time - Months from End. Enter “0” in the adjoining field.
•
Start Rate - Previous.
•
End Time - Months from Start. Enter “30” in the adjoining field.
•
End Rate - 1.
•
Decline Type - Historical Regression.
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3. Click OK.
4. Click Next. The forecast for ORANGE_23:Li_1C displays.
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Exercise 1
Create a Forecast
Using what you have learned, do the forecast for this well. Save
the forecast. The trend from mid-1994 to the last historical date could well
determine the well’s behavior for forecasting.
Exponential Fit Type
1. Click Next. The graph for ORANGE_26:Cl_3 displays.
For this well, the last historical rate is below the economic limit. Therefore, no
default forecast can be carried out. The production (decline) trend of this well
is easily identified. However, the forecast will be stopped before the end of the
forecast period due to the forecast rate reaching economic limit first.
2. Set the lower limit to exclude the first and the last production data points as
desired.
3. From the Properties pane, set the Fit Type to Exponential.
4. Select Edit>Scenario.
5. Select the Forecast tab.
6. Select Last Fit Rate from the Start Rate list.
7. Click OK.
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8. (Optional) If you select Best Fit from the Method choices, OFM will use
hyperbolic regression in this case. Still the forecast will stop before it
reaches the time limit. Save the forecast.
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9. Take a look at the legend. The Forecast Ended By field reads “Rate”. That
means the specified End Rate is met before the forecast End Time.
10. Click Next. The forecast for ORANGE_31:De_1 displays.
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This well has produced consistently throughout its production history.
Somewhere in the second half of 1997, the well experienced an increase in
production, and the decline trend for this well should follow this trend instead of
the overall trend that takes into account data points from previous production
periods.
11. Set the lower limit as shown in the image below.
12. Select Edit>Scenario.
13. Select the Forecast tab and enter 150 (to verify the well reaches
economic limit before the time limit) in the adjoining field of Ending
Time>Months from Start.
14. Click OK.
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Save the forecast.
Read the legend. The remaining reserve is about 31 Mbbl. The value of EUR
is about 347 Mbbl. The Forecast Ended By field is Rate.
However, separate analyses suggest that the well has about 40 Mbbl in
remaining reserve, or about 355 Mbbl in total reserve. We can schedule
reserve (or specify total reserve) and ask OFM to adjust decline rate to
reserve.
15. Select Edit>Scenario.
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16. Select the Forecast tab.
17. In the Schedule Reserves field enter 40.
18. In the Decline Parameters Rate field select Calculate from Reserves
and Schedule Time.
19. Click OK. The forecast displays.
20. Edit the Scenario again. Clear the Schedule Reserves list field.
21. In the Total Reserves field enter 355.
22. Click OK and do not forget to read the legend to verify the results. The
graph displays.
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23. Save the forecast.
24. Click Next. The forecast for ORANGE_32:Li_1C displays.
Study the production history of this well. The behavior from mid-95 to mid-98,
and the one from mid-99 on could well be the trend for our forecast. However,
there is a period of anomaly (from mid-98 to mid-99) that needs to be
reckoned for.
25. Set the lower limit to take into account the production period from mid-95
to mid-98.
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26. Select Edit>Scenario.
27. Select the Forecast tab.
28. From the Start Time list, select Date, and then enter 19980630 in the
adjoining field.
29. Set the Start Rate list to From Fit.
30. Select Months from Start from the End Time list, and enter 84 (including
2 years from mid-98 to the last historical date).
31. Select Reserve Type of Possible.
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32. Click OK. You are returned to the Scenario Manager.
33. Click Close. The graph displays.
34. Save the forecast.
35. Click Next. The forecast for ORANGE_34:Ad_1A displays.
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ORANGE_34:Ad_1A has short historical production data. The limited data for
this completion shows a sharp drop in production, which may indicate this is a
troubled well. However, the last data point does not follow the generic trend,
and it could be incorrect if we decide to use the overall best fit (dictated by the
first five data points) or the partial fit through the last two data points. It has
been suggested that this well may be put on production for a short period of
time and be shut in to perform corrective measures and then put back on
production following the partially fitted trend (Decline Rate of about 0.05 M.e.).
All these operations/parameters can be reflected in your forecast estimation,
using multiple-schedule forecast technique.
2. Select Edit>Scenario.
3. Select the Forecast tab. We can see that the well will have about four
more months before reaching10 bbls/d, which is a fairly good shut-in rate.
4. From the End Time drop-down list, select Date and enter 20001031 in the
adjoining field. The End Rate and Reserve Type are of insignificance in
this example.
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1. From the Properties pane, set the Fit Type to Hyperbolic.
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5. Click Add. Schedule #2 displays.
6. From the End Time drop-down list, verify Months from Start is selected,
and enter 6 (months) in the adjoining field.
7. In the Oil Advanced Settings group box, check the Days Off options and
enter 31 (days) in the adjoining field.
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9. From the End Time list, verify Months from Start is selected and enter 50
(months) in the adjoining field.
10. Select Unproven for Reserve Type. In the End Rate field enter 1 (bbl/d)
as the desired limit.
11. In the Decline Parameters section of the dialog, from the Type list field
select Exponential.
12. In the Decline Parameters Rate field select User Defined and enter 0.05
(M.e.) in the adjoining field.
13. In Oil Advanced Settings, check Shut In Effect and enter 300 (%) in the
adjoining field.
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8. Add Schedule #3. From the Start Rate list, select Change By Percent
and enter 300 (%) in the adjoining field.
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Creating a Forecast Analysis
14. Click OK.
Exercise 2
Shut in activities
Experiment other ways to simulate shut in activities in this well.
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15. Click Next. The forecast for ORANGE_34:Ad_3BU displays.
This well has a very short and erratic production history. Therefore, it is nearly
impossible to determine a trend of any kind. A different approach must be
used to estimate the forecast for this well. Studies show that this well has all
the same parameters as a nearby well, which we know the trend.
16. Right-click on the graph and select Digitize Points (or select Edit>Digitize
Points).
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17. Click the points where you believe the best-fit line should be (For your
reference, review the magenta points selected on the graph - you may
want to zoom in from the View menu).
18. When finished, right-click and select Done. The best-fit line is redrawn.
Reset the zoom on the graph if needed. The graph is redisplayed.
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19. Save the forecast.
20. Click Next. The forecast for ORANGE_34:Li_1C displays.
This looks like a very reasonable forecast. The well has excellent production
trend but ask yourself why there are no production data after August 1999.
You may want to rule out data points before the peak production (early time) to
obtain a better fit.
21. Set a lower limit to rule out the first five data points. The best-fit line should
then be hyperbolic.
22. Select Edit>Scenario.
23. Select the Forecast tab.
24. Select Last Historical Date from Start Time drop-down list and From Fit
from Start Rate list.
25. Click OK.
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The next three wells, ORANGE_35:Ad_1A, ORANGE_35:Ad_3BU, and
ORANGE_36:Li_1C all have very brief and erratic production history.
Study those three wells and perform the forecasts for them. Do not forget to
save your forecasts when done.
26. Select the last well from the filter list, RED_4:Cl_3 (you can do it from the
drop-down well list).
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This well has good history, and there might have been a work over near the
end of 1986, which really revitalized its production. Thus the trend should be
determined from that time on.
27. Set the lower limit and upper limit so the used points are as shown:
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28. Once you are satisfied with this forecast, save it.
Question
Now that we have done the forecasts on the selected wells, how
do we view the forecast results?
Manual Match for Empirical Solutions
OFM will initially plot control points based on historical or digitized data
regression. Once a control point is moved, manual match method is
automatically activated and the user will have total control of how the match
should be performed. Users have the ability to interactively adjust the
regression parameters by using the mouse to change the shape and position
of the fit curves. The manual match mode remains active until the match
method is changed to Auto in the Properties pane.
Note: There are constraints in the manual matching algorithm (i.e. constraints
to the movement of the control points). For example, if the fit type is set to
exponential you cannot move the control points to make a hyperbolic
regression line.
OFM Forecast performs historical regression automatically by default when
using empirical solutions.
1. Select Blue_5:Sc_0 from the Step pane.
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2. To view Historical Regression results, click the Historical Regression tab
located at the base of the Forecast window.
On the Historical Regression results pane you can see that the best fit for the
historical data is hyperbolic decline with an R-squared (R^2) value of
0.902190.
There are three data points (in blue color) on the historical fit curve. These
points are Control Points, which control the shape and position of the fit curve
during manual match process. The control points are initially calculated using
the equation obtained from auto match. The number of control points are
determined by the decline type (or the relationship between dependent and
independent variables) and the number of to-be-determined parameters. In
the example shown there are three control points, which are used to determine
initial flow rate (qi), b value and initial decline rate (Di).
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3. Select a control point and then drag it.
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Creating a Forecast Analysis
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Note: You can also move the fit curve selecting it and dragging it. If you want
to move the curve do not position the mouse over the control point. This will
only result in moving the control point.
Note the match method property on the property pane is now set to Manual.
During manual match process the parameters (qi, b, and Di) are calculated
instantaneously based on the control points, and their position to the X- and Yaxis as you dragging and moving them.
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Viewing the Forecast
Chapter 2
Forecast
Even though you can generate forecast from monthly, daily, or even sporadic
data, the forecast (rate) results in OFM are stored in monthly frequency. By
default, OFM activates four report tabs, Historical Regression Report, Forecast
Report, Summary Report, and Database Forecast Report. You can close any
of these tabs from the View menu as desired or by selecting the tabbed page
and clicking the Close button.
Learning Objectives
In this section, you will be introduced to viewing the forecast. You will
successfully learn how to perform the following procedures within this
workflow:
•
Create and compare cases
•
Use the auto decline feature
Using the Output Features
Note: The next steps assume that you are on the last well, RED_4:Cl_3, and
have saved its forecast results to the database.
1. Select the Historical Regression tab and the following displays.
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Viewing the Forecast and Output Window Features
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This tabbed page enables you to read the information about your (real)
historical data and the fitted data, the fit equation, and its correlation
coefficient.
Note: To anchor the window, click the push-pin in the upper right corner. The
vertical push-pin indicates that the auto-hide feature is turned off. Refer to the
image below.
2. Drag the vertical scroll bar to view the portion of fitted rates.
Note: In this tab or in any other tabs of the Output Window, you can right click
to access a text-editing menu to copy/paste, format the fonts, or save the
information to a text file.
3. Select the Forecast tab.
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Viewing the Forecast and Output Window Features
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This tabbed page enables you to read the forecast (decline) equation, forecast
rates and cumulatives/reserves. Scroll down to see the rest of the report. If you
have multiple scheduled forecasts, each schedule has its own equation.
4. Select ORANGE_34:Ad_1A from the well name drop-down list, select the
Forecast tab (in Output Window). The information pictured below displays.
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5. Scroll down to see the rest of the report.
6. Select the Summary tab.
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7. This tabbed page contains a summary of your forecast, per schedule.
Select RED_4:Cl_3 again from the well list (and reselect the Summary
tab).
8. Select the Database Forecast tab.
Remember that you may set up your forecast and keep working on it without
saving the result. OFM keeps a copy of your working forecast, so you can
compare and evaluate your case. Once a forecast is saved to your database,
you will have two forecast results displayed in this Database Forecast tab; one
is of the saved forecast, and the other one is of the work-in-progress forecast.
9. Right-click on the graph and select Limits>Reset.
10. Set a lower limit as shown.
This is our working forecast, which uses a hyperbolic regression instead of an
exponential regression in case1. The working forecast results in higher
forecast rates, especially towards the end of the forecast period.
11. Click on the Database Forecast tab in the Output Window (you may want
to resize this window), scroll down and view the result. The results shown
are of the saved forecast (case1).
Note: Remember that the current forecast (working) is not saved yet; you
cannot retrieve other information (i.e., equations, correlation coefficient, etc.).
Working with Cases
1. Select File>Save to Different Case. The Case dialog displays.
2. Name the new case Case2. The rest of the fields are optional.
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3. Click OK.
4. Select the Database Forecast tab and scroll down. You can see that the
Database Forecast Rate and Volume now reflects the information of
Case2.
Note: Once you add a new case to the database, your working forecast is
defaulted to that new case (but not saved until you do so).
5. Select File>Cases. The Case window displays. You can see that Case2 is
checked (denoting the active case).
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6. Click OK to close the window.
7. Now that you have more than one case saved to the database, you can
select to compare the results of those two cases and view the comparison
in the Output Window.
8. Select Tools>Compare Cases. The Current Case, as mentioned earlier,
is the active case - Case2.
9. Select Case1 from the Compare Case drop-down list.
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10. Click OK.
11. Select the Compare Cases pane (OFM automatically activates this pane
when you set up Compare Cases).
12. Scroll down to see the rest of the comparison report.
Note: To deactivate the Compare Cases pane, select Tools>Compare
Cases and select None from the Compare list. Upon clicking the OK button,
the Compare pane will disappear.
Auto Decline
Another useful tool regarding basic forecasting is Auto Decline. If you have a
filter list that contains many wells and would like to set up a baseline forecast
case for all the wells in the list, you can do it via Auto Decline. This feature is
designed to give users a baseline, and most of the time would not yield the
best-forecast possible for every well. You are strongly advised to check and
modify (if needed) every individual forecast afterwards.
13. Select Tools>Auto Decline. The Auto Decline window displays.
The following options are available from this dialog:
•
Cases - Assigns the case name.
•
Default Scenario - Restores the default values.
•
Scenario - Sets up the scenario.
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Viewing the Forecast and Output Window Features
•
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Range - Specifies the data range.
OFM also provides the grouping option that pre-groups data before performing
the forecast and facilitates output control options as saving/printing, etc.
14. Click OK.
Exercise 3
Auto Decline Feature
Experiment with this Auto Decline feature.
Exercise 4
Perform Forecast Analysis
Perform the forecast on gas phase for a well of your choice.
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Additional Forecasts
Chapter 3
Additional Forecasts
In the previous session, we used Rate vs. Time decline model to forecast the
rates and reserves. OFM also allows other common types of forecasting
approaches using other variables such as Water Cut, Cumulative Production,
and P/Z, etc.
Learning Objectives
In this session you will spend some time with two other forecasting models,
Water Cut vs. Cumulative Oil and P/Z vs. Cumulative Gas. You will
successfully learn how to perform the following procedures within this
workflow:
•
Water cut versus Cum.Oil analysis
•
Use grid map tools
Water Cut versus Cum.Oil Analysis
1. Select ORANGE_32:Li_1C from the well list.
2. Select Edit>Scenario Manager. The Scenario Manager dialog displays.
3. Select the default scenario and click Edit.
4. From the Variable Association section of the dialog, select Water Cut for
Phase/Analysis. Make sure you have Time set to Date, Oil.Cum for
Cum.Oil, and Water.Cut for Water Cut.
5. Click OK. The Edit Scenario dialog closes and you are returned to the
Scenario Manager.
6. Click Close.
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Notice that since we did not specify the Limiting Water Cut, OFM uses 95%
water cut for the cut off point, while the starting water cut is already higher than
95%, resulting in no forecasting at all. Therefore, you will need to specify the
limiting water cut.
7. Select Edit>Scenario Manager. The Scenario Manager dialog displays.
8. Select the Default Scenario and click Edit. The Edit Scenario dialog
displays.
9. Select the Historical Regression and Forecast tab.
11. For End Water Cut, select the Value radio button and enter a value of 99
(%) in the adjoining field.
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10. In the Forecast section of the dialog, for Start Water Cut select the Last
Historical radio button.
Additional Forecasts
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12. Click OK. Then click Close. The graph displays.
Take a look at the Reserves and EUR. Since the starting water cut is already
high, there is not much that we can do.
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13. Select Edit>Scenario.
14. Select the Forecast tab. For Starting Water Cut select Value and enter
98 (%) in the adjoining field.
15. Click OK then Close. The graph displays.
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Notice that even with a little lower water cut, you can increase the reserves. If
you lower the starting water cut even more, the reserves will be increased
significantly. However, that is not a good approach in this case.
16. Set up a lower limit on this curve as shown.
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Additional Forecasts
The graph refreshes.
17. Now that you know the value of EUR (~331 Mbbl), and Remaining
Reserve (~14 Mbbl), you can get back to the Scenario and schedule your
reserves correspondingly.
Exercise 5
Schedule Your Reserves
Switch the phase back to Oil; schedule your reserves (Remain or
Total).
P/Z vs. Cum.Gas Analysis
In most of OFM projects, pressure data is not adequately available. For each
individual well, you may find a scattered set of pressure information, yet
usually not enough to conduct an effective analysis. Fortunately, many wells
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Additional Forecasts
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may belong to the same entity (i.e. reservoir), and have comparable
properties. With other parameters being similar (relatively), their pressure data
could also be of the similar ranges. OFM provides this capability of plotting
discrete individual pressure points versus grouped (combined) cumulative gas.
As the name suggests, we need pressure and gas production data, as well as
PVT information. In this lesson, we will create a P/Z vs. Cum.Gas forecast to
determine gas recoverables.
1. Check the PVT information first. Select Database>PVT. The PVT Entity
Name dialog displays.
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2. You should have at least one PVT profile (named Default) in your PVT
Entity Name list. Select one, and click Edit. The Edit PVT Information
dialog displays.
3. Select the PVT Data tab.
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Additional Forecasts
4. Click OK.
5. Close the PVT Entity Name window.
6. The next thing to do is to load some pressure data into this project. In this
Demo2005 project, there is a field in Monthlyprod table named Pressure.
That is the field we want to load pressure data into. We will interactively
add in pressure data from the Data Editor.
Note: You may want to use the Data Loader to load them in, yet you need to
create the data file first.
7. From the Filter pane, click the
by Completion dialog displays.
Filter by Completion icon. The Filter
8. Select GREEN_6:Li_1C, ORANGE_19:Ad_1A, and RED_4:Cl_3 from
the list. Click OK.
9. Click Next button, well GREEN_6:Li_1C displays.
10. Select Database>Data. The Select OFM Table to Edit dialog displays.
11. Select the Monthlyprod table from the table list.
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Additional Forecasts
12. Click OK.
13. In the Pressure column, enter the following:
2900 at 1/1/1981
•
2700 at 2/1/1982
•
2500 at 5/1/1983
•
2300 at 1/1/1985
•
2200 at 12/1/1985
•
2000 at 7/1/1989
•
1900 at 1/1/1992
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•
14. Click away from the last cell.
15. Click Next to move to ORANGE_19:Ad_1A and enter the following:
•
3500 at 1/1/1973
•
2800 at 8/1/1981
•
2650 at 3/1/1982
•
2400 at 11/1/1984
•
2100 at 3/1/1987
•
1850 at 11/1/1992
16. Click away from the last cell.
17. Click Next to move to RED_4:Cl_3 and enter the following:
•
3000 at 4/1/1980
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Additional Forecasts
•
2500 at 1/1/1983
•
2000 at 3/1/1988
•
1900 at 7/1/1990
•
1800 at 11/1/1992
•
1700 at 4/1/1994
18. Click away and then close the editing window.
19. Select Group Data then select Analysis>Forecast to open a forecast
window (if you do not already have one opened).
20. Select Edit>Scenario Manager and click Edit.
21. Make the selections shown in the image below.
22. Click OK for the graph to be displayed.
Take a look at the graph; you can see all individual well’s pressure points
plotted together against the combined cumulative gas production. Since we
did not specify the initial, current, and abandonment P/Z, OFM uses its default
(calculated) values there.
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Additional Forecasts
23. Select Edit > Scenario Manager. The Scenario Manager dialog displays.
Click Edit.
24. Verify that the Phase/Analysis is set to PZ and select the Historical
Regression Forecast tab.
25. Enter the following:
•
4000 (psia) for Initial P/Z
•
1800 (psia) for Start P/Z
•
800 (psia) for End P/Z
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26. Click OK. Observe the result from the Legend box.
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27. Select Edit > Scenario Manager. The Scenario Manager dialog displays.
Click Edit.
28. Select the Historical Regression Forecast tab. Select From Fit for
Current P/Z and unlock Initial P/Z (you will let OFM determine those
values).
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29. Click OK.
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Additional Forecasts
Exercise 6
Performing Gas Forecasting
Return to the Forecast Scenario, switch the phase to gas and
perform gas forecasting using the reserves obtained in this lesson.
Question
Compare the result with previous result. What kind of conclusion
can you make from this analysis?
30. Click Next to move to GREEN_6:Li_1C. The forecast graph displays.
Exercise 7
Performing Additional Analyses
Perform P/Z vs. Cum.Gas, then Gas Rate vs. Time analyses on
the other two wells. Save the results.
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Fetkovich Type Curve Analysis
Chapter 4
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Fetkovich Type Curve Analysis
In the last chapter, you have used the empirical solution method to forecast
production. That method is based on a set of decline equations (documented
in the Online Help, under DCA equations), which also is fundamental for a
more advanced technique, Fetkovich Type Curve.
Fetkovich Type Curve Analysis uses a set of “type curves” representing the
typical performance of ideal (conventional) finite radial (flow) reservoirs.
Production data for the entity are plotted against time on a dimensionless loglog scale. The plotted (real) curve is then matched with one of the provided
Fetkovich curve, and the real entity can be referenced to the ideal curve.
The ideal Fetkovich log-log type curve analysis assumes that the well rates will
decline after a period of pseudo-steady state, denoting by a rather flat
(constant) rate when it is plotted against time on a log-log scale.
Technically, Fetkovich Type Curve Analysis (TCA) is designed for late-time
history matching and should not be applied to early-time analysis. Users are
required to “re-initialize” data (to the first point, or close, where the rates start
declining).
Learning Objectives
In this section, you will learn the basics of Fetkovich TCA functionalities in
OFM2005. More advanced analytical skills regarding this method will be
addressed in the higher levels of OFM training. You will successfully learn how
to perform the following procedures within this workflow:
•
Use Fetkovich TCA
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Fetkovich Type Curve Analysis
•
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Perform Type Cure Match
Using Fetkovich Type Curve Analysis (Late-Time)
1. Clear any previously applied filter.
2. Expand the Well List node in the Filter pane and select
Prod_Wells98.txt.
3. Select BLUE_5:Sc_0.
4. Open a Forecast window.
5. Add a new case named Case3 to the project, so you will not override the
previous forecasts.
6. Select Edit>Scenario Manager and set this scenario as the default then
click Edit. The Edit Scenario dialog displays.
7. Associate the following on the Flow Model tabbed page.
Notes:
•
When you select Fetkovich Type Curve from the Solution list, the other
parameters in Model Description section of the dialog are grayed out.
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Fetkovich Type Curve Analysis
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The known set of reservoir parameters that Fetkovich TCA uses can
be read from there.
•
If you have dynamic (data loaded into a table, i.e. monthly) pressure
data and want to use them, associate the variable at the Flowing
Pressure list. Otherwise, you can enter (static) pressure values in the
Pressure group box.
•
Once you select either Fetkovich Type Curve or Analytical Transient
from the Solution drop-down list, the Historical Regression tab (in
Empirical method) disappears and substituted by the Parameters tab.
8. Select the Parameters tab and accept the default parameters to start
history matching.
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9. Click OK. The graph displays. (You will have to add the header, resize the
graph, legend to get the desired output)
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Fetkovich Type Curve Analysis
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10. Reinitialize your data by right-clicking on the graph. A shortcut menu
displays. Select Reinitialize.
11. Position your cursor at your desired data point and click to highlight the
point.
12. Right-click and select Done from the shortcut menu.
Note: OFM may display a dialog with a Reinitialize Data Tip as shown below.
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Fetkovich Type Curve Analysis
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13. Click OK. Your data has been reinitialized.
Note: You can also adjust the data fitted curve (Dark Green) by positioning the
cursor over that curve and when a hand appears, click the curve and drag it to
your desired location then release the mouse.
15. Select Tools>Typecurve Match. OFM runs the matching algorithm and
returns the following:
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14. Position your cursor over the real curve until the cursor changes to a fourheaded arrow, drag it and move it (remember the “initial” point of the
decline period) closer to the displayed type curves.
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Note: You may get a failure message as the result of this operation. In this
case, go back to the Scenario>Parameters tab and adjust the values of your
matching parameters and re-run the Typecurve Match command. If you have
any questions, please feel free to seek help from your instructor.
16. Select Edit>Scenario.
17. Click on the Parameters tab. Observe that after running the matching
algorithm, OFM returns the calculated results for the b value and
Permeability, Skin factor, Drainage area (if you are performing both earlyand late-time analysis).
18. Select the Flow Model tab and clear the Late-Time Only checkbox (just
an exercise).
19. Close the dialog and rerun the matching algorithm. The program returns a
set of parameters.
20. Clear b value and Permeability boxes, check Skin factor and enter 45 in
the Estimates box, check Drainage Area and enter 300 in the Estimates
box.
21. Click OK.
22. Select Tools>Typecurve Match. The new result returns:
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Question
Compare this with the previous result, what do you see?
23. Select Edit>Scenario.
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24. Select the Parameters tab.
Based on the returned skin factor, you would have a good idea of what the
next estimate Skin factor should be. Remember that you can vary all four
parameters in your matching criteria.
25. Check the Permeability box, and enter 30 (md).
26. Check the Skin factor box, and enter 60.
27. Check the Drainage area box, and enter 700 (acre).
28. Check the b value box, and enter 0.3.
29. Click OK. If required, re-initialize your data.
30. Select Tools>Typecurve Matching. The graph displays and the results
reported in the Legend box are different.
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Fetkovich Type Curve Analysis
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31. Edit the Scenario. Select the Parameters tab and examine the return
values of the matching parameters.
Keep repeating the operation by supplying better estimates, running history
match, until you get a good match. Do not forget, these parameters are really
important. By changing the values of Wellbore Radius, Net Pay, and Porosity,
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the magnitude of your matching parameters is strongly affected. For example,
you can run the matching algorithm with this set of parameters:
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Note: Sometimes you will get a matching failure message. One of the
reasons could be that it does not converge after a certain number of iterations.
Click on the Matching Calculation Settings and this window appears:
Note: You can select to match on production rate, incremental production, or
cumulative production. You can also specify the number of iterations and the
tolerance.
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Fetkovich Type Curve Analysis
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32. After running the matching algorithm, OFM returns the calculated match
parameters (which normally will be different than the estimates you
entered). Click on Update to use the Results as Estimates for the next run,
or click on Revert the other way around.
Remember, the settings on your Forecast tab are of your default setting
(Current Scenario).
33. Select Tools>Forecast. OFM will run the forecast and display the forecast
results.
Note: Review the values of your reserves in this forecast. You may want to
compare it with the forecasts of other methods.
Question
Examine the results. What conclusion can you make?
34. Select Edit>Scenario.
35. Check the Late-Time Only box, and all the pressure information is grayed
out.
36. Click OK.
37. Move the real curve closer to the type curves, and then select
Tools>Typecurve Match. The result displays:
Note the values in the Legend box. It looks like we’ve got better reserves.
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38. Select Edit>Scenario and select the Parameters tab. You can see in
Late Time analysis, the only matching parameter used is the b value.
Note: After running Fetkovich Type Curve analysis (Late Time and all), your
matching parameters can be used back in Empirical Solution method to get a
better decline estimation.
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Analytical Transient Solutions
Chapter 5
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Analytical Transient Solutions
Fetkovich Type Curve method uses a particular set of reservoir parameters. The
applicability of Fetkovich TCA is somewhat limited. OFM allows users to specify
different types of reservoirs/formations, based on the phase and the technique
that they select to pursue. The new solution (only available in OFM 2002 and later
versions) is called Analytical Transient Solution, handling a variety of different
parameter combinations. In other words, you can always claim that Fetkovich
TCA is a special case of Analytical Transient Solution.
The usage of Analytical Transient Solution is very similar to Fetkovich TCA,
except that you have to describe your model. Therefore, the users are required to
know more about their reservoirs/formations to effectively use this tool. Unwanted
results could be the product of incorrectly specifying reservoir parameters and/or
matching criteria.
Learning Objectives
•
Set up basing forecast case
•
Combine all three solutions
Using Analytical Transient Solutions
1. Make sure that you have a forecast window opened. Select BLUE_5:Sc_0
from the well list.
2. From the Properties pane verify that you are on Oil phase.
3. Select Analytical Transient Solution from the Solution list.
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In this section, you will learn to set up a basic forecast case using Analytical
Transient Analysis. (Advanced training on this topic is addressed in other OFM
courses.) We will then pull everything that we have learned together to combine
all three solutions to perform the forecast on a well that does not have good
production data (or does not even have production data). You will successfully
learn how to perform the following procedures within this workflow:
Analytical Transient Solutions
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4. Select the Parameters tab. To be consistent with what we did in the
Fetkovich TCA lesson, enter the following values:
•
Wellbore Radius - 0.2 (ft)
•
Net Pay - 20 (ft)
•
Porosity - 0.3 (fraction)
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Analytical Transient Solutions
5. Click OK.
6. If your curve has not been reinitialized (from the previous exercise), do it now.
7. Select Tools>Typecurve Match.
Exercise 8
Compare the Results
8. Select Edit>Scenario and select the Parameters tab. Take a look at the
returned (matching) parameters:
9. Compare these values with ones obtained from previous Fetkovich TCA. With
the formation parameters the same, model description the same, what would
possibly be the contributing reason(s) for the differences (if any)?
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Compare this result with the one you obtained using Fetkovich TCA
previously. What kind of conclusion can you make? (Pay attention to the model
description.)
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10. Select the Flow Model tab. Describe the model as shown below.
Note: Depending on your associated choice in the Model Description, your next
choice (in that description) and your match parameters list change.
12. Click OK to display the graph. Re-initialize your data.
13. Move the real curve closer to the type curves (and the fitted data curve) and
select Tools>Typecurve Match.
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11. Select the Parameters tab. Specify a Skin Factor of 45 and a Fracture
Conductivity of 500. Uncheck the other parameters.
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Analytical Transient Solutions
14. Examine the results on the graph and legend box. Notice that with your model
description, you see more type curve parameters such as Cr, Skinf, etc.
Examine the results from the Output Window and experiment with the match
parameters by different combinations and estimate values.
Exercise 9
Perform an Analytical Transient Analysis
Pick a well of your choice and perform Analytical Transient Analysis
on it. Save the result when you are satisfied with it.
Note: Let your instructor know what you find in your experience. There will be a
lot of interactive learning with this kind of analysis and environment.
The next exercise demonstrates the capability of combining all three types of
solutions you have learned to forecast oil production on a well that has a brief
production history.
15. Select BLUE_1:Ge_6 from the well list.
16. The (Empirical) forecast may display. Notice that with only a few data points,
a visual trend may be unreliable. Assume that we know the reservoir model
and have formation parameters available; we could start the forecast from a
different approach.
17. From the Properties pane select Empirical solution.
18. Change the Fit Type to Hyperbolic method.
19. Locate the b Value properties. Set the Method to User and enter User value
of 0.6.
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Note: During this lesson, you will probably encounter quite a few “Type Curve
match failure” messages. It is due to either incorrect parameter specifications or
the algorithm not converging. Remember that you can specify your own Matching
Settings. If needed, change the matching criteria (i.e. match on cumulative rate
instead of production rate, increase number of iterations/tolerance). Always keep
in mind that anything that you make may affect the validity of your results.
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20. Select Edit > Scenario. The Current Scenario dialog displays.
21. Select the Forecast tab and specify the following:
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22. Click OK and the graph shows (you may have to set the limits).
23. Save the forecast.
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24. Select Edit>Scenario.
25. Select the Forecast tab and add Schedule #2.
26. For this schedule, use Analytical Transient Solution method and specify
the following on the Forecast tab:
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27. Enter these values on the Parameters tab:
28. Click OK.
29. Select Tools>Typecurve Match.
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30. Save the forecast.
31. Select the Forecast tab in the Output Window and find the section for
Schedule #2.
32. Select Edit>Scenario.
33. Change Schedule #2 to Empirical.
34. Click OK. The graph displays (both working and saved forecasts).
Note: Pay attention to the saved forecast (in Cyan), you can distinguish the two
portions of the curve, with different hyperbolic b values.
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35. Select Edit>Scenario.
36. Add Schedule #3.
37. On this schedule, use Fetkovich Type Curve.
38. Specify the following on the Forecast tab:
Start Time – Months from End
•
Start Rate – Previous
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End Time – Months from Start and in the adjoining field 36 months
•
Decline Type – Exponential
•
Decline Rate – User Defined and in the adjoining field 0.3
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•
39. Click OK.
40. Select Tools>Typecurve Match.
41. Save the forecast.
42. Click on the Forecast tab (Output Window) to check the result.
43. Switch back to Empirical to see the saved forecast.
Exercise 10
Pick a well that does not have good production history (or one that
does not have production at all) and do the forecast.
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44. Close the forecast window.
45. Clear the filter and return to the Basemap.
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Retrieving Forecast Results
Chapter 6
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Retrieving Forecast Results
Forecast information (reserves, rates, etc.) can be retrieved via calculated
variables and displayed/used in other modules such as report, plot. In this
session, we will create variables to return rates on group and individual wells.
We will then create variables to return remaining reserves and estimate
ultimate recoverables. We will use the forecast results saved in Case1.
Prerequisites
Knowledge of calculated variables, plotting, and reporting is a prerequisite in
this lesson. If you have any problems, refer to the Online Help (or any training
material that applies).
Learning Objectives
In this section, you will successfully learn how to perform the following
procedures within this workflow:
•
Create variables to return remaining reserves
•
Estimate ultimate recoverables
•
Use forecast result
Calculated Variables
1. Create a calculated variable named FCST.OilonGroup to retrieve forecast
oil rates on a group of wells. The definition of this variable is:
FCST.OilonGroup = @Forecast( date, "oil", "Case1", "group" )
2. Assign unit to the variable accordingly.
3. Create a calculated variable named FCST.GroupofOil. This variable adds
individual forecasts (oil rates) together for a group of wells. The definition
of this variable is: FCST.GroupofOil = @Forecast( date, “oil”, “Case1”,
“sum” )
4. Assign unit to the variable accordingly.
5. Create a calculated variable named FCST.RemRes. This variable
retrieves (oil) Remaining Reserves for the selected entity (group/well)
based on the specified case. The definition is: FCST.RemRes =
@DcaResults( "oil RES", "Case1", 1 )
6. Assign unit and multiplier to the variable.
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7. Create a calculated variable named FCST.EUR. This variable retrieves
(oil) Ultimate Recoverables for the selected entity based on the specified
case. The definition is: FCST.EUR = @DcaResults( "oil EUR", "Case1",
1)
8. Assign unit and multiplier to the variable.
9. We will use these variables on the report first.
10. From the Filter pane, expand the Well List node. Right-click, select Open
and select the Prod_Wells98.txt file.
11. Group the data.
12. Select Analysis>Report to open a report window.
13. Select Edit>Report Parameters. In the Select section of the Edit Report
dialog enter Date, Monthlyprod.Oil, FCST.OilonGroup.
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14. Click OK. The report displays.
15. Select Edit>Report Parameters. Add FCST.GroupofOil to the report.
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16. Click OK.
17. Use the Next and Previous buttons to navigate through all the wells. As
you can see, for individual well the group and the sum options are the
same. Thus for individual well, you can even omit this last argument in the
variable definition, i.e. @Forecast( Date, “Oil”, “Case1” ).
18. Add the other two variables (FCST.RemRes and FCST.EUR) to the
report.
19. Group the data to regroup all the wells in the list.
Constant values of Reserves and Recoverables are reported. These values
are the results of your forecast on the group, not the sums of individual
reserves and recoverables.
Exercise 11
Verify Report Results
Bring up a Forecast window and verify the results (by comparing
the retrieved values on the report and the saved values on the forecast).
20. Create a variable named FCST.OilRate. The definition is: FCST.OilRate =
@Forecast( Date, "Oil", "Case1" )
21. Associate the unit properly to the above variable.
22. Add FCST.OilRate to the report as shown below.
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23. Click OK.
24. Scroll down to see the results.
25. Select Tools>Settings>Group. The Settings dialog displays.
26. Check the Sum individual well forecasts when grouping wells option.
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Notice that if you omit the last argument, the @Forecast() function takes the
“group” option. (In other words, “group” is the default option). If the variable has
been created this way (without the last argument) you still want to retrieve the
summed values, you can specify an OFM option from the Tools>Settings
menu.
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27. Click OK. Regroup the wells and the report displays.
28. Verify the result. Reverse the operation (by clearing that group option).
Exercise 12
Create Variable to Retrieve Data
Select a few wells and perform forecast on gas phase. Save them
to another case. Create variables to retrieve forecast gas rates, reserves, and
recoverables.
29. Select Analysis>Plot. The Edit Plot dialog displays.
30. Add the following variables - Plot Oil.CalDay, FCST.OilonGroup and
FCST.GroupofOil versus Date. Your plot should look similar to the one
pictured below.
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31. Navigate through all the wells in the list and see their plots. On individual
well, the two forecast variables are the same. You should expect to see
the forecast portion consistent (in trend) to the historical portion. Example:
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Exercise 13
Create Bubble and Grid Maps
Create bubble map and grid map of oil RES and EUR.
Notes:
•
@Forecast() function can only retrieve rates
•
@DcaResults() function retrieves constants (i.e., forecast parameters)
•
If you perform forecast using ratios or cuts and would like to retrieve
those variables, use the @DcaCalc() function
Congratulations! You have completed the OilField Manager – Forecast
Analysis Fundamentals course.
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