Citrine Guided Session #3 Decline Curve Analysis · Decline Curve Analysis 1. Introduction This...

Citrine v1.22 © DeGolyer and MacNaughton – KAPPA 2013-2016 Citrine Guided Session #3 • CitGS03 - 1/10

Citrine Guided Session #3

Decline Curve Analysis

1. Introduction

This guided session will demonstrate the process of applying empirical decline curve equations

within the Citrine Analysis module. For this guided session, we will utilize the previously created

project that comes with the installation package.

2. Default Suite

Open ‘Citrine Guided Session 3 – Start file.kc1’ file (it can be found in the Guided Session data

in the ‘Downloads’ section of the KAPPA website).

Switch on the ‘Analysis’ module by clicking on .

The set of plots displayed in the Analysis module is referred to as ‘suite’. The settings of suites

can be accessed via ‘Suite’ element of the main toolbar. There are three default graph suites in

the Analysis module: ‘Rate Data only’, ‘Rate and Pressure’, ‘DCA’. Citrine will automatically

choose between the first two depending on the presence of pressure data for any of the wells.

The user can create a new one by choosing plots from the list of predefined ones or adding

customized (‘Suite Create’), and any suite can be modified (‘Suite Edit’).

For this exercise switch to the ‘Default: DCA’ suite by selecting ‘Suite → Open’ in the main toolbar

(Fig. 2.1).

The ‘Default: DCA’ graph suite consists of the following plots:

b-factor vs. Production Time (Log-Log)

Decline vs. Production Time (Log-Log)

Rate vs. Production Time (Semi-Log)

Cumulative production vs. Production Time (Cartesian)

Rate vs. Cumulative production (Semi-log)

Rate Cumulative Ratio vs. Production Time (Log-Log)

The lasso selection options can be used to filter outliers: select none,

exclude/include data, and select all.


Fig. 2.1 – Default Decline Curve Analysis Graph Suite

3. Selecting a Decline Model

In order to select models to apply to the well data, first click the ‘New Model’ button on the

toolbar. This dialog presents the list of the empirical decline models available within Citrine.

For this Guided Session choose the Modified Hyperbolic model for Field_A_Well_01 and click

‘OK’. You can always return to this dialog by clicking the same button to add another decline

model.

Fig. 3.1 – Model Selection dialog


4. Application of the Decline Model

Once the model is chosen, the active suite is updated with lines representing the model and its

derivative curves. Initial estimation of model parameters is performed. Model parameters can

be adjusted to obtain a match with the data as will be described below.

Before proceeding, let us explore the ‘Decline Curve Settings’ dialog, accessible via ‘Options →

Decline Curve Settings’ in the main toolbar. The user can select rate/time abandonment limits

in order to estimate an EUR value (Fig. 4.1).

Fig. 4.1 – Decline Curve Settings / EUR Abandonment Criteria

The ‘Results’ field on the toolbar menu displays the estimated EUR value based on the model

parameters and the production abandonment limits (Fig. 4.2).

Fig. 4.2 – Model settings and EUR estimate display

Clicking ‘Parameters’ button in the ‘Models control’ section opens the model-specific parameters

and regression menu. Fig. 4.3 displays the Modified Hyperbolic model parameters. For example,

the D Limit parameter defines the constant terminal decline (the exponential tail).

The parameter fields have both numerical input and slider bars. One can manipulate the model

sliders or directly type values into the fields to simultaneously match the well data on all the

active plots of the selected suite. Alternatively, nonlinear regression can be performed to obtain

a better match. The user defines the parameters to be regressed upon with an option of assigning

higher weight to cumulative production.

In the bottom left section of the Model parameters window specific EUR settings for the selected

model can be set to override the global settings.


Fig. 4.3 – Modified Hyperbolic Model parameters dialog

Segments may be added to any decline curve model by clicking on the ‘Edit’ button next to the

Segments list. The menu bar will change to the segment menu, which allows the user to define

a split point by either time, cumulative production or a point on the plot (Fig. 4.4). In this

example we will not split the model into segments, so click ‘Cancel’.

Fig. 4.4 – Segment Selection dialog

Now let us create a model for the first well in the list. Make sure that ‘Field_A_Well_01’ is selected

as ‘Well’ from the drop down menu at the top left. Create a new model by clicking on and

select ‘Modified Hyperbolic’ from the list to create a model for the well data analysis. Click on

‘Parameters’, include the b value into regression by ticking an appropriate checkbox and run the

regression by clicking ‘Improve’.

The model match for Field_A_Well_01 is shown in Fig. 4.5. Note that the estimated EUR value

updates with any change to the model parameters.


Fig. 4.5 – Modified Hyperbolic Match for Field_A_Well_01

5. Comparing Models

Model results and forecasts can be compared directly on one plot. Switch to the ‘Default: Rate

Data Only’ suite (‘Suite Open’). For the same well, Field_A_Well_01, create Duong, Power-

Law Exponential and Stretched Exponential models and adjust parameters for each of the models

to match the data in the same way as described in the paragraph above. Tick the ‘Show all

models’ flag on the Model control toolbar (Fig 5.1) to display all the models at once.

Fig. 5.1 – Models control

Zoom out on the Gas Rate vs. Time log-log to see the forecasts. Fig. 5.2 depicts the plot with

the Modified Hyperbolic (Brown), Power-Law Exponential (Black), Stretch Exponential (Reference

model, bold Blue), and Duong (Green) matches for Field_A_Well_01.

Untick ‘Show all models’. You can change the reference model by ticking an appropriate box in

the ‘Models control’ toolbar section when the chosen model is selected.


Fig. 5.2 – Model Comparison for Field_A_Well_01

6. Multiwell Processing

Multiwell processing dialog is available by clicking the ‘Multiwell Processing’ button in the ‘Models

control’ section of the toolbar or under ‘Analysis Multiwell Processing’. The option creates a

chosen model for each of the selected wells simultaneously.

There are two ways of defining multiwell processing. One is creating a model for all the wells in

a list in one go starting from scratch. Another way is to take parameters estimates from an

existing decline match for one of the wells to be transferred to a number of other wells.

Let us first consider creating models directly. Make sure that in the top left corner a well without

any models is selected in the list, e.g. Field_C_Well_01. Click on the ‘Multiwell Processing’ button.

To create a modified hyperbolic model for several wells in one go, select Fields C and D wells in

the list, then choose ‘Modified Hyperbolic’ under the ‘Selected Model’, set all the regression

parameters as Variable, and click ‘Start’.


Fig. 6.1 – Multiwell Processing dialog

Close the dialog window and go through the chosen wells to verify that a model ‘Modified

Hyperbolic #01’ was added for each of the selected wells with independent regression run on

model parameters. You can improve the matches individually by refining the regression results.

An example of the match for Field_C_Well_01 is presented in Fig. 6.2


Fig. 6.2 – Multiwell Processing dialog

Before proceeding, switch to the ‘Default: Rate Data Only’ suite.

When a model is present for an active well (shown in the top left corner of Citrine window), the

model parameters could be used as input for creating models for other wells. Select

Field_A_Well_01 in the list, then select ‘Power-Law Exponential #1’ as the active model (it was

created at the previous step).

Click on the ‘Multiwell Processing’ button. Note that the model type is now automatically set to

the active model type (Power-Law Exponential), and the user has an option of fixing regression

parameters at the values from the current well’s model (Fig. 6.3). Keep the n and D_inf value

found for the reference well to be used in matching the model to the other wells’ data, and set

the two other model parameters (qi and D) as Variable. Select both wells from Field C as target

wells by ticking them on the list. Click ‘Start’.

Go through the wells to observe that the target wells were updated with the Power-Law

Exponential model. The chosen wells from Field C have good correspondence to the selected well

decline.

You can perform the same exercise with wells from Field D to see that the parameters from

Field_A_Well_01 are unsuitable to obtain a match and further adjustment of the parameters is

required.


Fig. 6.3 – Multiwell Processing dialog starting from an active model

You can see the list of all the wells in the working set with all the models that have been created

in the browser. It is called by clicking on (Fig. 6.4). The active well/phase/model are

highlighted in blue, they can be changed by clicking on ‘Select’. A model can be deleted in

browser with the ‘Delete’ button.


Fig. 6.4 – Analysis module browser

7. Analyzing Statistical Wells

The decline curve analysis workflow described in the preceding sections can also be applied to

the statistical wells (see calculation of the statistical curves in §8 of the Guided Session 2). If

any statistical curves have been previously saved in the Diagnostics module of Citrine, they will

appear in the list of the wells.

It is noted that statistical curves are stored for the working sets for which statistics were

performed. For example, if a user performs statistics for ‘Working Set A’, statistical curves will

be available when ‘Working Set A’ is selected in the Analysis module.

The decline curve analysis process described above can be applied to statistical wells in order to

forecast production and calculate EUR values.

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