pForecast User Manual
pForecast User Manual
Software as a service solution to digitalize, simplify, and standardize how production forecasts are generated and utilized.
Table of Contents
3. Forecast Configuration
3.1 Create a Forecast
3.2 Subsurface Input and Configuration
3.2.1 Production Potentials
184.108.40.206 Fraction Resources
3.2.2 Forecast Wells
220.127.116.11 Injectors Wells
3.2.3 Production Correlation
Table of Figures
Figure 1: Defining the user’s role (part 1).
Figure 2: Defining the user’s role (part 2).
Figure 3: Asset selection.
Figure 4: Asset configuration.
Figure 5: Facility configuration.
Figure 6: Setting up a hierarchical structure for a multi-facility asset.
Figure 7: Cluster configuration.
Figure 8: Wells configuration and uploading of historical data from Excel.
Figure 9: Excel template for uploading historical production per well.
Figure 10: Import historical production data from CDF.
Figure 11: Quality control of imported historical data per well.
Figure 12: Uploading fuel and flare input data.
Figure 13: Excel template for uploading fuel and flare input data.
Figure 14: Creating a new field on the asset level.
Figure 15: Applying PVT properties for voidage calculations.
Figure 16: Defining the voidage group.
Figure 17: RNB profiles and projects.
Figure 18: Creating a table of factors for conversion of production volumes to sales volumes.
Figure 19: Sales conversion template.
Figure 20: Creating a new reporting scheme.
Figure 21: Creating tags.
Figure 22: Creating report groups.
Figure 23: Creating report groups by importing an Excel file.
Figure 24: Creating ownership groups.
Figure 25: Generating gas lift curves.
Figure 26: Creating a new forecast (part 1).
Figure 27: Creating a new forecast (part 2).
Figure 28: Access to the forecast properties.
Figure 29: Uploading well production potentials.
Figure 30: Configuration of well production potentials.
Figure 31: Configuration of forecast wells.
Figure 32: Creating injector wells.
Figure 33: Injection schedules template.
Figure 34: Creating uncertainty group.
Figure 35: Uploading production efficiency schedule.
Figure 36: Production Efficiencies schedule template.
Figure 37: Providing PE values in tabular format.
Figure 38: Controlling the dependencies on PE in an hierarchical facility structure
Figure 39: Boost factor schedule.
Figure 40: Planned shutdowns schedule template.
Figure 41: Defining planned shutdowns manually.
Figure 42: Defining planned shutdowns manually.
Figure 43: Adding capacity constraints.
Figure 44: Creating a separation forecast.
Figure 45: Creating a well to be drilled.
Figure 46: Creating a drilling schedule.
Figure 47: Rig availability configuration.
Figure 48: Non-drilling schedule configuration.
Figure 49: Creating a scenario (part 1).
Figure 50: Creating a scenario (part 2).
Figure 51: Access to the scenario properties.
Figure 52: Activation of wells in operation (a.k.a existing wells).
Figure 53: Activation of wells to be drilled.
Figure 54: Activation of PE schedules.
Figure 55: Activation of constraints.
Figure 56: Activation of reporting schemes.
Figure 57: Running a stochastic simulation (part one).
Figure 58: Running a stochastic simulation (part two).
Figure 59: Description of correlation options.
Figure 60: pForecast result viewer.
Figure 61: Available profiles in pForecast.
Figure 62: Gantt Charts for drilling schedules.
Figure 63: Creating a new corporate roll-up (part 1).
Figure 64: Creating a new corporate roll-up (part 2).
Figure 65: Creating a new corporate roll-up (part 3).
Figure 66: Creating a new corporate roll-up (part 4).
Figure 67: Creating a new corporate roll-up (part 5).
Figure 68: Creating a new corporate roll-up (part 6).
Figure 69: Creating a new incremental profiles analysis (part 1).
Figure 70: Creating a new incremental profiles analysis (part 2).
Figure 71: Creating a new incremental profiles analysis (part 3).
Figure 72: Creating a new incremental profiles analysis (part 4).
Figure 73: Creating a new incremental profiles analysis (part 5).
Figure 74: Creating a new incremental profiles analysis (part 6).
Figure 75: Slot recovery or sidetrack.
Figure 76: Modelling a slot recovery.
Figure 77: Capacity upgrade with facility shut-in during upgrade.
Powersim Software is a Norwegian company based in Bergen. Powersim Software provides a family of business tools tailored to forecast and analyze complex dynamic problems. pForecast, which has been developed for predicting oil and gas production, is one of these tools. pForecast is an uncertainty-centric software that digitalizes, simplifies, and standardizes how production forecasts are generated and utilized. pForecast performs a full lifetime simulation of the production and injection forecast, including historical data, in keeping with the industry’s ever-increasing need for agility.
This manual covers the essential steps to get started with the pForecast software. For users seeking specialized support, please reach out to us at:
Email: pForecast@powersim.no Phone: +47 55 60 65 00
pForecast is a SaaS solution with a user-friendly and interactive interface, offering a simple and consistent methodology for production forecasting. It performs deterministic and stochastic analyses and generates unbiased production forecasts considering the involved uncertainties for the entire field. pForecast consolidates the forecasting and acts as a common framework across assets.
pForecast, which uses Monte Carlo simulations at its core, improves analysis quality as uncertainties are an integral part of the forecasting, not added as a deviation on a deterministic run. The software applies to both short and long-term forecasting.
pForecast’s hierarchical structures consist of three levels: asset, forecast, and scenario. This manual shows how to configure each level and generate a comprehensive production forecast. A short description of each chapter is given in Table 1.
Running the Simulation
pForecast is accessible through the web browser. The users need to request access to pForecast via their company IT support. Users can be assigned different roles at the corporate level as well as per asset. For each role, there are associated access rights. For an asset, the following roles and their respective access rights are applicable:
- Administrator: Allowed to administrate asset, e.g., assign users to roles
- Contributor: Allowed to work with forecasts
- Editor: Allowed to work with forecasts and flag forecasts for review
- QC: Allowed to work with forecasts, flag forecasts for review, and approve/reject forecasts
- Subscriber: Allowed to view forecasts
Figure 1 and Figure 2 show how the users’ roles can be defined for each asset.
After selecting the asset, you will see the following page, on which you can assign the roles:
An asset or a business unit in the pForecast context is a group of fields that share data. When a user is given access to an asset, the user can be given read-only or read-and-edit access. The access provided applies to the entire asset. The first time the users start pForecast, they need to select the asset they are working on. The left-hand side navigation bar has a button called “Select asset.” The user can choose or switch between different assets by clicking on this button. See Figure 3.
When the asset of interest is selected, the user is presented with the following screen (Figure 4), where it is possible to configure the asset by pushing the properties button in the top-right corner.
Asset configuration is for setting up static input that does not usually change or require frequent updating. There are five main areas to choose from: Facility, Field, Reporting Schemes, Ownership Groups, and Gas Lift Curve Sets. Under each of these areas, there are additional parameters that can be set, as detailed in the following structure:
- Fuel and Flare
- Sales Conversion
- Reporting Groups
In the following sections, you will find an explanation of how to configure these parameters.
The user can select an existing facility or create a new one by pressing the “Create new” card. When a facility is selected, it is possible to edit or delete it. It is worth noting that if the facility is deleted, all associated data are deleted. Figure 5 depicts how to make a new facility.
In the oil and gas industry, it is common to find multiple production facilities within a single asset. This practice serves several purposes, driven by the following factors:
• Large field size: Some oil and gas fields are characterized by their significant size and abundant reserves. To efficiently extract and process the hydrocarbons from such fields, it becomes necessary to establish multiple production facilities. These facilities encompass drilling platforms, processing plants, storage tanks, and other crucial infrastructure elements. By distributing the production capacity across various facilities, operators can optimize the extraction process and ensure that the asset reaches its full potential.
• Geographic dispersion: In certain instances, an oil and gas asset comprises multiple fields that are spread across a vast geographic area. Each field may possess distinct characteristics, such as varying reservoir pressures or different types of hydrocarbons. To address these unique requirements and maximize operational efficiency, multiple facilities are strategically deployed. This approach enables operators to tailor production and processing operations according to the specific needs of each field, minimizing logistical challenges and enhancing overall performance.
• Expansion and tie-in fields: Oil and gas assets often undergo development in stages. Initially, a production facility is designed and constructed to handle the output from primary fields. However, as new fields are discovered or tie-in fields are integrated into the asset following the initial development, the existing facility’s capacity may prove insufficient. Consequently, additional facilities are built, or existing ones are expanded to accommodate the increased production volume. This adaptive approach allows for seamless integration of new fields into the asset’s infrastructure.
Within the pForecast software, users have the capability to simulate the segregation of phases within a single facility, exporting specific portions of production while redirecting the remaining volumes to another facility. Additionally, the system allows for the modeling of dependencies in facility uptimes, which arise when multiple facilities share power units or processing plants.
Figure 6 shows how, under the facility properties, you can set up a two-level hierarchical structure for a multi-facility asset, in order to model separation of phases at child facilities as well as dependencies on PE and shutdowns in the hierarchy.
Clusters are used to group wells and to constrain the production and injection to the capacity of that group. Clusters can be routed to other clusters; there can be up to four levels of clusters in a facility. Later, when configuring forecasts, you can attach constraints to the clusters defined here. When the “Clusters” tab is selected, it is possible to create, edit, and delete clusters. When the plus icon is clicked, the cluster dialog box appears. It is possible to give the cluster a name. The name must be unique. It is also possible to specify an existing parent cluster. If no parent is specified, the cluster will be a top-level cluster. Figure 7 shows how clusters can be created and structured.
The most crucial feature of wells in the pForecast software is to hold the production history. pForecast has two notions of a well. Firstly, it is a physical well, as detailed here; secondly, it is a forecast well that connects to the physical well. The forecast well connects to a wellbore of a given physical well, and each well must have at least one wellbore to get the historical production over to the forecast. Wells can be created, edited, and deleted. Figure 8 depicts how historical production and injection data can be uploaded from Excel. Figure 9 shows the Excel template for uploading historical production per well.
Historical production data can also be imported from Cognite Data Fusion (CDF). Once the connection is set up, pForecast will collect updated historical data from CDF daily.
Figure 10 shows how to configure for import of historical production data from CDF.
After importing production data through either Excel sheets or CDF, for quality control, you can open the “History details” menu for each well and observe the production and injection profiles for different fluids (see Figure 11).
Both fuel and flare are calculated at the facility level as linear functions of produced and injected volumes. The fuel and flare calculated per facility are distributed to the contributing wells for sales calculations based on one of the following methods:
- Liquid volume (use as the default)
- Gas volume
- Oil volume
- Sum of produced oil, gas in oil equivalents and water
- Sum of produced oil, gas in oil equivalents, produced water, injected gas in oil equivalents, and injected water
The below formula will be used to distribute the fuel based on the liquid volume method:
The other methods follow this pattern.
In pForecast, fuel and flare input data can be imported through an Excel file or edited manually using the embedded table. See Figure 12 for more details.
Figure 13 shows the available Excel template in pForecast for uploading fuel and flare input data.
The user can select an existing field or create a new one on the asset level by pressing the create card. You can define as many fields as needed. When a field is selected, it is possible to edit or delete it. If one of the fields is deleted, all associated data is deleted. Figure 14 illustrates how to create a new field.
Voidage groups use PVT properties. Constant PVT properties are assumed to be sufficiently accurate to model injection to achieve a reasonable voidage replacement. PVT properties can be edited by selecting the PVT Properties tab. PVT properties can be created, edited, and deleted. When the plus icon is pressed, PVT properties can be set, and the following parameters are entered: formation volume factors for oil and gas and solution gas oil ratio. The formation volume factor for water is assumed to be unity. Figure 15 indicates how to apply PVT properties.
Voidage groups are used to model required injection volumes. The groups are created here and used later when a scenario is built. When the voidage tab is selected, it is possible to create a new one and edit or delete the selected voidage group. In the field properties, the following page appears when the “Voidage” tab is pressed. A unique name must be entered, and a set of PVT properties, defined in the previous step, must be selected. By applying the target voidage factor as a fraction, pForecast will steer the injection rates to reach the target voidage factor. See Figure 16 for more details.
A structure of RNB profiles and projects can be defined for a field. These profiles and projects are used to aid in reporting data to the Revised National Budget (RNB) in Norway each autumn, 15 October. An RNB profile is a set of profiles given to the authorities. The Norwegian Petroleum Directorate (NPD) allows up to 15 profiles with annual reports on recoverable resources in classes 0 to 5. Projects in resource classes 6 and 7, which are reported separately in the RNB reports, are to be placed in profile 0. The reader is referred to the NPD website for more information about resource classification. Each profile should be given a unique name and a profile number.
When the RNB Profiles tab is selected, it is possible to create a new RNB profile or to edit or delete the selected profile. See Figure 17 for more details.
For a field, the user can define yearly or monthly entries, each containing various parameters related to conversion from production to sales figures. If a set of parameters is provided for both a month and the year of that month, the month data will be used in calculations. In the case that there is no provided entry for a month, the defaults for the various parameters will be used. See Figure 18 for more details.
Figure 19 shows the available Excel template in pForecast for uploading sales conversion parameters.
A reporting scheme is used to define how the simulation results are aggregated and output. pForecast calculates the production rates per well, and reporting schemes enable the users to define what groups of wells they wish to output production rates for. It is possible to define multiple reporting schemes.
Each forecast well is assigned one ‘tag’ that describes a property of the well. In fact, a well can only be assigned one tag per reporting scheme. The tags must therefore be disjoint, meaning the properties do not overlap. Examples of properties used to define tags are which reservoir the well produces from, which production license it belongs to, if the well is a producer or injector, and so on and so forth.
On the other hand, tags are collected into one or more report groups. The report groups will be used to output results containing the sum of production from all wells assigned tags belonging to the report group. To sum up, the steps for configuring a reporting scheme in pForecast software are:
1. Create a new reporting scheme
2. Define the tags that will be assigned to the wells
3. Define the report groups that will be output in the results and assign well tags to the report group.
4. Assign tags to the specific wells in the forecast. This step is performed in the forecast configuration.
In pForecast, reporting schemes can be defined either by populating the provided Excel file and uploading it or by creating them manually. Figure 20 demonstrates the process of creating a new reporting scheme, Figure 21 showcases the creation of tags, and Figure 22 explains the creation of report groups. On the other hand, Figure 23 demonstrates the method of importing an Excel file to accomplish the same task.
For an asset, the user can define a set of ownership groups consisting of ownership shares for sales oil, gas, and natural gas liquid (NGL).
A forecast well, defined under forecast properties, can subsequently connect to an ownership group. The various ownership shares are used when calculating net sales values. In other words, wells are tagged to ownership groups to characterize the company’s ownership share of the produced volumes. It is also possible to define a default ownership group; in that case, all wells that have not been specifically tagged to an ownership group will be assigned to this group. Suppose there is no default ownership group for the asset, and a well is not assigned to a specific ownership group. In that case, pForecast will assume 100% ownership share as the default value when generating net sales profiles. In that case, the net sales and the gross sales are equal.
Figure 24 shows how to create an ownership group step by step.
For an asset, the user can define gas lift curve sets, consisting of curves that give the relationship between the fraction of gas lift potential and the fraction of production potential for given water cuts. A production profile, which is defined under Forecast Properties, can subsequently connect to a gas lift curve set. The gas lift curves are used in connection with constraint calculations involving gas lift. Figure 25 shows how to specify gas lift curves.
Forecast configuration provides future projections for three main input data domains: subsurface, facility operations, and drilling. The following sections give details on creating a forecast and configuring previously mentioned input data.
The first step is to create a new forecast. It is worth mentioning that if the user selects to duplicate a forecast, the original one is kept, and changes in the duplicated forecast are not reflected in the original. It is also possible to edit or delete the selected forecast. See Figure 26 and Figure 27 for more details.
After creating a new forecast, the following page will be shown, in which the user can provide high-level forecast properties and time ranges:
After making a new forecast, the user can easily access all properties (see Figure 28).
For a forecast, the user can define a set of production profiles to be used by forecast wells of type producers to establish their production potential. The potential is given as a rate per stream day, where a stream day is 24 hours when running at full capacity under optimal conditions. Generally speaking, pForecast supports six types of production profiles:
- Stream day rate vs. month
- Stream day rate vs. delta month
- Fractions vs. delta month (see section 18.104.22.168)
- Decline curve
- Multi-segmented decline curve
- Stream day rate vs. accumulated volume
The actual production (given as a rate per calendar day) can be different from what the input production potential profile would suggest since the production is affected by various factors such as production efficiency, shutdown periods, and capacity limitations. In addition, potential profiles can be set to be volume-based. The production volumes can be quite different than the input production potential profile would suggest. To adjust for this, the user can specify that the production profile is to be calculated using a volume-based profile rather than a time-based. In order to have the correct relationship between time and produced volume, the user should enter an average production efficiency applied in the establishment of the production profile. In addition to using volume-based potentials for production estimation, it is possible to cut the production based on a given produced volume, a given cut-off rate, a time limit when drilling a new well starts, or any combination of these.
The production potential for the well is imported from an Excel file, and for the first time, a new profile will be created and appear in the list. When production potential is uploaded for a profile that already exists, the new data will overwrite the old data.
After importing, a list of the production profiles is shown. A unique name for each production profile is shown together with the type of production profile. It is also specified whether the profile is generic or not. Different forecast wells can reuse a generic production potential profile. The list also shows how many times the production potential profile is used by forecast wells, noted by use count. The dates for the creation and last modification of the production potential profile are also shown.
Figure 29 and Figure 30 display how to upload and configure well production potentials.
After uploading the well potentials, click the pen icon to enter the menu for potential configuration. More details are shown in Figure 30.
The fraction resources profile type (Fractions vs delta month) is very similar to the delta monthly profile type. The values you provide on a monthly basis represent the proportion of the resource volume. Typically, the sum of all your fraction monthly values should add up to one. If this condition is met, the entire resource volume will be produced during the specified relative months.
Example: let’s say you have a resource of one million Sm3. Normally it would take 400 months to produce this resource, however, for the sake of simplicity, let’s assume that the total production time is five months. In that case, the five production fractions could be: [ 0.3, 0.3, 0.2, 0.1, 0.1 ]. That will give a production volume per month of [ 300.000, 300.000, 200.000, 100.000, 100.000 ]. So far, this is quite straightforward. This input could also work fine if we change our resource to 900.000 Sm3. In that case we would get another scale on our production, only by changing the resource value: [ 270.000, 270.000, 180.000, 90.000, 90.000 ]. In many cases you want to do this, because the shape of your profile remains the same for many resource volumes. pForecast requires input about how much the resources will decrease over time. This is given in a separate Excel sheet containing resource values versus time. This could for example mean that if the well starts producing in 2027 the resource will be one million Sm3, but if it starts producing in 2035, the resource will be 900.000 Sm3. By giving this in the ‘’VsTime’’ Excel sheet, pForecast will interpolate the resource volumes in the years between. The same monthly fraction values will be used regardless of the resource volume which is dependent on the production start time.
The user can create, edit, and delete forecast wells by selecting the “Forecast well” tab. A list of forecast wells is presented. It is worth mentioning that when the production potential for a well is uploaded for the first time, a new forecast well will automatically be created and appear under the tab “Forecast Well.” The list shows the name, whether this well is already in operation (or whether it is a drilling target), and the facility the forecast well belongs to. It is also shown how many times the forecast well is used in scenarios and the dates for the creation and last modification of the forecast well.
After clicking on the “Forecast well” tab, the user should click the pen icon to enter the menu to configure the forecast well. A unique name for the well should be given. The well should be linked to a facility. The production efficiency of the well typically depends on which facility the well is connected to. The default set is used if the well is not connected to any facility. Users can specify production efficiency forecasts for all facilities and the default set. It is also possible to override the production efficiency for a particular well by choosing a specific production efficiency forecast for the well. A forecast well that is in operation is typically linked to a wellbore. The production history is taken from the given wellbore. No history is included if the well is not linked to any wellbore. The forecast well can also be linked to a cluster. A cluster is a group of wells that share the same capacity, and this capacity limit may constrain the well. Another option is to link a well to a voidage group. The voidage groups are used for calculating injection requirements. No producing wells are influenced by this, but injection can be reduced according to voidage requirements. The well can also be linked to an uncertainty group. It is also possible to assign the well a tag per reporting scheme. See Figure 31 for more details.
Under the “Forecast well” tab, injector wells can also be created, and provided a target rate schedule for injectors.
The user must supply a start year and a start month for the injection control. The user then provides a mode for the injector. The mode can be one of the following:
• Water injection
• Gas injection
• Water Alternating Gas (WAG) injection
A priority is given to all wells within the same cluster. If an injection constraint is exceeded, the higher priority wells are kept on injection. The target rate for water and gas are entered. If the well does not belong to a voidage group, the well is kept on the target rate if injection constraints permit it. If the well belongs to a voidage group, the target rate may be reduced to match the production level of the voidage group. If the injection mode is selected to be WAG, then the user must supply WAG duration in months. If the well injects gas, the gas formation volume factor for the injection gas (Bg) should be entered. Figure 32 shows more details about injector well configuration.
Figure 33 shows the available Excel template in pForecast for uploading injection schedules.
The well can also be linked to an uncertainty group. An uncertainty group is used to correlate the production of a collection of wells in stochastic analyses. In fact, the group’s correlation factor is used to define the strength of the wells’ interdependency. It is also possible to have negative dependencies (correlations). For instance, for a group of two wells, a negative correlation would mean a relationship in which one well’s production increases as the other’s decreases and vice versa. Figure 34 shows the steps toward making an uncertainty group.
After creating an uncertainty group, the user can assign production wells to the uncertainty groups under the “Forecast well” tab. The created uncertainty group will now be an option in the dropdown menu (see step 9 in Figure 31).
Normally, the uptime for the production facilities is close to 100%. In pForecast, in addition to most likely values for production efficiencies (PE), it is possible to provide upside and downside cases. Users can create, edit, and delete PE forecasts by selecting the “Production Efficiency” tab under the forecast menu. A list of PE forecasts is presented. The list shows the name and the facility the PE forecast belongs to. It is also shown how many times the PE forecast is used in scenarios (use count) and the dates for the creation and last modification of the PE forecast. Figure 35 illustrates how to upload the PE forecast from an Excel file.
Figure 36 shows the available Excel template in pForecast for uploading PE forecasts.
The user can also specify monthly and annual estimates for the production efficiency manually by filling out the embedded table. It is also possible to choose distribution type and boost factors. See Figure 37 for more details.
If you have previously set up a two-level hierarchical structure for a multi-facility asset at the asset level, you can control dependencies on PE (Production Efficiency) within the hierarchical facility structure. These dependencies are established for PE forecasts of child facilities in the two-level hierarchy. A correlation factor determines how the PE values of a child facility are related to the PE values of the parent facility. It is important to note that negative dependencies (correlations) are allowed. This implies a relationship in which one facility’s PE increases as the other facility’s PE decreases, and vice versa. Furthermore, you have the ability to specify that the PE values of the child facility will never exceed those of the parent facility under any circumstances. See Figure 38.
Boost factors model boost production after a long shut-in of a field. After such a stop, many fields experience significant changes in water cut, gas-oil ratio, or well potential until the production stabilizes after a period of production. In order to model this, it is possible to specify a monthly boost factor in a boost factor schedule and connect this schedule to the PE forecast. Each phase rate is then multiplied by the boost factor for that phase for the year and month specified. Users can create, edit, and delete boost factors by selecting the “Boost” tab. A list of boost factor schedules is presented. The list shows the name of the boost factor. It is also shown how many times the boost factor schedule is used in scenarios and the dates for the creation and last modification of the boost factor schedule. The boost factor schedule dialog box appears when the plus icon is clicked. A unique name for the boost factor schedule should be entered. It is then possible to add, edit or delete individual boost factors from the list in the dialog box. When a new boost factor is entered, the user must supply the year and month for the boost and the boost factors for oil, gas, and water. See Figure 39 for more details.
In addition to PE values, planned shutdowns can also be considered. For instance, in case of scheduled shutdowns due to facility maintenance, turnarounds (TAR) can be defined, and it is possible to assign uncertainties both to the start date and the duration of these scheduled shut-ins.
In a two-level facility hierarchy, a child facility’s PE forecast can incorporate shutdowns from the parent facility’s PE forecasts. When inheritance is enabled, you will observe potential shutdowns from the parent PE forecasts mixed with the shutdowns specific to this PE forecast. For each inheritable shutdown, you have the option to choose whether to inherit it or not. If there are multiple PE forecasts for the parent facility, the inherited shutdown descriptions will include the respective PE forecast names as prefixes.
It’s important to note that inheriting a shutdown from a parent PE forecast does not activate the shutdown in a scenario unless that specific PE forecast is also included for the parent facility. In other words, you can opt to inherit shutdowns from multiple PE forecasts, and the final decision regarding activation depends on the inclusion of the respective PE forecast for the parent facility. See Figure 42
Users can add constraints by selecting the “Capacity” tab under the forecast properties section. It is also possible to copy, edit or delete selected constraints. When the plus icon is selected, the user can create a new capacity constraint. The user must enter a name and indicate from when the constraint is valid. A constraint is valid from this point in time and onwards until a new constraint is entered. Maximum values for oil, gas, water, and liquid production are entered along with maximum values for the injection of water and gas. Regularity factors for the injection can also be entered. Figure 43 shows more details.
In a forecast, users can define separation forecasts, which provide monthly estimates for the phases’ separation before routing to the next level of the cluster hierarchy. These forecasts help users understand how the phases progress and distribute within the hierarchy, aiding in planning and decision-making. Figure 44 shows how to create a separation forecast.
For a forecast, the user can define a set of wells in operation and drilling targets (wells to be drilled). The two types are both referred to as forecast wells. It is worth mentioning that a forecast well is not to be confused with a physical well defined under the asset level. The latter is used to hold the production history, and an in-operation forecast well typically connects to a wellbore of a physical well in order to get the historical production over to the forecast. Figure 45 shows how to create the undrilled wells.
The next step is to set up drilling schedules. The list under the “Drilling” tab shows the name of the drilling schedule and which facility it belongs to. It is also shown how many times the drilling schedule is used in scenarios and the dates for the creation and last modification of the drilling schedule. A drilling schedule can be created, and the selected drilling schedule can be copied, edited, or deleted. A unique name should be entered for each drilling schedule. A description can also be given. The drilling schedule can be linked to a facility. If it is linked to a given facility, only wells from that facility can be included in the drilling schedule. The start date of the drilling schedule must be provided. In addition, the user can specify a rig availability schedule. A rig availability schedule is a forecast of how much time the rig is used for drilling. This factor is given as a yearly efficiency factor. Non-drilling periods can also be specified. These are planned periods when the rig is not drilling. These periods are provided with a fixed start date and duration, including uncertainties. Finally, the sequence of wells on the drilling schedule is shown in a list. Wells can be added or removed from the list. A selected well can be easily moved up or down in the sequence. Figure 46 shows how to create a drilling schedule.
Normally, the rig cannot be utilized for drilling the entire time it is in operation. Maintenance on the rig itself and other activities on the platform may prevent drilling operations. These activities are either planned or unplanned. In pForecast, unplanned periods without drilling are entered as rig availability. While planned work can be entered as non-drilling periods with fixed start times and uncertain duration. Let us first take a look at unplanned periods. A rig availability factor is an expression of how much a drilling rig is used for drilling wells. The rig availability is entered as a percentage on an annual basis and influences the drilling schedule performance. Selecting the “Rig Availability” tab presents a list of rig availabilities. The list shows the name and the facility the rig availability belongs to. It is also shown how many times the rig availability is used in scenarios (use count) and the dates for the creation and last modification of the rig availability. Rig availability can be created, and the selected rig availability can be copied, edited, or deleted. The rig availability form appears when the plus icon is clicked. A unique name should be entered, and a facility to link to. The rig availability for each year is entered in the table as a percentage. If no rig availability is given, pForecast assumes it to be 100%. See Figure 47 for more details.
On the other hand, planned periods when no drilling takes place are modeled as non-drilling periods in the pForecast software. Typical examples are plant maintenance stops, major rig upgrades, or when the license owner has decided not to drill wells for an extended period. A non-drilling period is assumed to have a fixed start point in time. The stop duration is given alongside low and high estimates for the duration. The user can create, edit, and delete the non-drilling schedule by selecting the “Non-drilling” tab. A list of non-drilling schedules is presented. The list shows the name of the schedule. It also shows how many times the schedule is used in scenarios and the dates for the creation and last modification. The non-drilling schedule form appears when the plus icon is clicked. The user should enter a unique name, description, fixed start date, and duration. The duration is entered together with low and high estimates. If the distribution type is set on triangular, the value of the duration can be assumed either as expected or as the most likely value. See Figure 48 for more details.
Scenario configuration is the last level of the pForecast hierarchical structure. A scenario is essentially a consumer of existing data and can also be seen as a version of a forecast. At this stage, it is possible to run different scenarios of the forecast and visualize, analyze, and compare results.
In order to create a scenario, the user should select an active forecast. After selecting the forecast, you will see the following overview page (Figure 49), where you can create a new scenario. After clicking the “Create the new scenario” button, the page in Figure 50 will be shown, allowing high-level scenario configuration.
After making a new scenario, the user can easily access all scenario properties (Figure 51) and start the configuration process.
Under the scenario properties, when the “Wells in operation” tab is selected, a list of existing wells in the current forecast is shown. The user can choose to include or exclude the wells in the current scenario. See Figure 52 for more details.
The next step is about wells to be drilled. When the “Drilling” tab is selected, the user can activate previously defined drilling schedules. It is worth mentioning that if a drilling schedule is activated, all forecast wells belonging to that drilling schedule will be automatically included in the scenario. Figure 53 gives more details.
The user can select the scenario’s active production efficiencies by selecting the “Production efficiency” tab under the scenario properties. The user is asked to provide a PE forecast for each facility. Different facilities may use the same PE forecast if appropriate. Each of the facilities in the model is shown in the list, and the PE forecast is chosen from the drop-down menu. See Figure 54 for more details.
As previously mentioned, (see section 3.3.4), a set of capacity constraints can be defined for a forecast. A constraint is given with maximum rates for production/injection as well as regularity factors for injection and is valid from a given point in time and onwards until a new constraint is activated. Each constraint is connected to a cluster in the hierarchical capacity cluster structure. Use the toggles under the “Included” column to determine which of these constraints to include in the current scenario. See Figure 55 for more details.
As mentioned earlier (see section 2.3), a set of reporting schemes can be defined for an asset. In order to configure reporting for a given scenario, the user should select the “Reporting” tab under the scenario properties. The user can choose which of these schemes to consider for the reports of the current scenario. In order to add, edit or delete group schemes, the user should go to the asset level and perform any necessary changes there. Figure 56 gives more details.
The simulator can be run in two different modes. The first mode is the deterministic mode. In this mode, it is possible to review the reference case without considering any uncertainties. The second mode is the stochastic mode, where a Monte Carlo approach is used to perform uncertainty analyses.
Figure 57 and Figure 58 show how to run a stochastic simulation.
After clicking the “Stochastic analysis” button, you will see the following page (Figure 58), where you can adjust the number of runs and start the simulation. The user can run between 10 to 2000 simulations and derive production profiles for different scenarios. It is recommended to run at least 200 runs for reporting purposes.
Before running the stochastic simulation, the user can specify how a series of events relate to each other. In fact, it is possible to choose how the correlation between events in a series should be carried out. Figure 59 shows how to set up the dependency between various events within a simulation run as a factor between zero (fully independent) and one (entirely dependent). For uncertainty groups, it is possible to set correlation factors between minus one and zero to model negative dependencies.
When the simulation is completed, the user is presented with the production profile results, including uncertainties. The results are shown for each report group. In pForecast, the user can choose between yearly or monthly plot granularity. It is possible to present both stream day rates (assuming 100 percent uptime) and calendar day rates (accounting for planned and unplanned downtime). Figure 60 shows how to navigate the result viewer under the “Profiles” tab.
In addition to production profiles, the user can easily generate other profiles, i.e., injection, fuel, and flare, as well as gross and net sales. Figure 61 shows an overview of available profiles in the pForecast software.
For Exploration and Production (E&P) companies, it is essential to take into account the uncertainties related to drilling. To meet this need, pForecast considers uncertainties involved in drilling programs, automatically generates Gantt Charts for drilling schedules and shows how uncertainty propagates over drilling targets. The user can view the expected drilling schedule by selecting the “Drilling” tab under stochastic analysis. If there is more than one drilling schedule, the user can select one of them by using the schedule dropdown list. The early start of drilling, expected start of drilling, expected end of drilling, expected start of production, and the late end of drilling are visualized for each well. Figure 62 provides more details.
In most cases, companies own multiple assets, and it is desired to see the cumulation of values for all or a few of these assets. The pForecast software can support corporate roll-up analyses, which are cumulations of values for a selected set of assets. The users can create as many roll-ups as they wish for corporate-wide analyses and reports. Figure 63 through Figure 68 illustrate how to create a new roll-up.
When creating a new roll-up, the following wizard page will be shown, in which the user can provide a name and description. It is also possible to insert the number of runs. The user can select a number between 100 and 10000. An automatic number will be used if this box is left empty. The automatic number is determined by selecting the larger value between 1000 and the number with the highest occurrence in the input (result sets). See Figure 64 for more details. Since corporate roll-ups consist of more than one asset, you will be asked to select the assets of interest in the next step. See Figure 65.
In the next step, for each of the assets selected in the previous step, a stochastic result set that is to produce the results for the asset during corporate roll-up should be specified. Figure 66 gives more details.
Now for each of the assets and result sets selected in the previous step, you need to specify which report groups from the result set that are to represent all wells, existing wells, and new wells of the asset during a roll-up. See Figure 67.
In the last step and after having provided the necessary information for the roll-up, you can specify if you want to view the roll-up once the wizard closes. Figure 68 shows how to do so.
Introducing new fields, new wells, or performing facility upgrades and maintenance affect the production of already producing fields. To support project investment decisions, incremental profile analysis can be performed to quantify the net production of the entire project.
Incremental profiles are based on two scenarios, a base case, and a new case, within the same forecast. In fact, the total production of the incremental profile is the difference between the base case and the new case. Figure 69 through Figure 74 illustrate how to create incremental profiles analyses.
When clicking the ‘Create new incremental profiles analysis’ card, the following wizard page will be shown, in which the user can provide a name, description, and the number of runs for the Monte Carlo simulation behind the analysis. The user can select a number between 10 and 2000. See Figure 70 for more details.
Since an incremental profiles analysis consists of two scenarios, in the next step, you need to select the base and new cases (see Figure 71). Note that the new case scenario is the one that includes the incremental project.
Next, you are required to select the report group which constitutes the basis for the increment calculations. This is normally a report group that represents the total project. In the incremental profiles analysis result viewer, the selected report group will result in three available report groups:
- Report group for the base case gross value
- Report group for the new case gross value
- Report group for the increment value
Figure 72 illustrates how to perform this step.
In addition to the report group that you have already specified, you can also include other report groups for quality check purposes. Similar to the previous step, for each selected group, three report groups will be available, base, new, and increment. Figure 73 shows how to select additional report groups.
After collecting all the necessary data for the analysis of the incremental profiles, you can decide whether you want to view the incremental profiles analysis once the wizard closes. See Figure 74.
This appendix presents how to deal with corner cases and how to combine functionalities in pForecast to model specific activities.
In case of modeling a sidetrack (Figure 75), pForecast can automatically shut down the existing well when the drilling of the new wellbore starts. Note that the new wellbore is secondary, and since the drilling times have uncertainty, we don’t know exactly when to shut down the old wellbore. In such cases, you would normally want to keep producing as long as possible. The solution is to connect these events by selecting the drilling start of the second wellbore as the cut-off condition.
To model a slot recovery in pForecast, first, you need to create a new wellbore. Figure 45 illustrates how to do so. Next, you need to select the “Production Potential” tab and select the profile used for the existing well you want to shut down. Then, under the Cut-off section, use the ‘’At drilling start of well’’ option. There you can choose a new wellbore; the one which is to replace the old wellbore. See Figure 76.
In connection with a capacity upgrade, it is necessary to define a shut-in period during the process of upgrading.
To model this, the old capacity should be valid before the shut-in period, while the new capacity should be valid from the end of the shut-in period. But since the duration of the shut-in period has uncertainty, the last day of the shut-in period will not be exactly known. To handle this issue, under the “Capacity” section we assign the “valid from-day” of the constraint to the start date of the shut-in period rather than to the end, even if the end would be the most correct time of change (see Figure 43).
Since it doesn’t matter which capacity we have during the shut-in; this approach will not compromise the validity time of the constraints before and after the shut-in.
To make this work, it is important to keep a fixed time for the start of the shut-in and use the same time for the new constraint. Figure 77 gives more details about how to model capacity upgrades in pForecast software.
This appendix summarizes the most used terminology in the pForecast software.
Asset: An asset in this context is a group of fields that share data.
Business Unit: Business unit and asset are used interchangeably.
Capacity limitation priorities: If capacity constraints limit your production, you have several ways of prioritizing the order in which wells will be choked. If you specify the default GOR or water cut, these values will be used instead of the calculated water cut or GOR. The priority groups are considered before GOR and water cut in a two-step prioritization approach. A low priority means being among the first wells to be choked and vice versa.
Cluster: Clusters are used to group wells and to constrain the production and injection to the capacity of that group. Clusters can be routed to other clusters; there can be up to four levels of clusters in a facility.
Corporate Analysis: Corporate roll-up analyses are cumulations of values for a selected set of assets. The users can create as many roll-ups as they wish for corporate-wide analyses and reports.
Cut-off: There are four criteria you may specify to cut the well production permanently: at a given rate, at a given volume, on a given date, and at drilling start of another well.
Field: An area in which there are one or several reservoirs. You import data for one field at a time. The field information is used for reporting purposes.
Gas Formation Volume Factor (Bg): This is the ratio of the gas volume at the reservoir condition to its corresponding volume at the standard condition (P = 101.325 kPa and T = 288.15 K). In pForecast, it is used for Voidage Management.
GOR: Gas-Oil ratio (Rs): This is the ratio of the volume of gas that comes out of the solution to the volume of oil at standard conditions (P = 101.325 kPa and T = 288.15 K)
Oil Formation Volume Factor (Bo): This is the ratio of the oil volume at the reservoir condition to its corresponding volume at the standard condition (P = 101.325 kPa and T = 288.15 K). In pForecast, it is used for Voidage Management.
PVT: This is the abbreviation for pressure, volume, and temperature.
Regularity: In pForecast, we use regularity for constraints on injection, which can be between zero and one. If you want to specify regularity for production, you should specify PE (Production Efficiency).
RNB: It is mandatory for operating companies in Norway to submit their forecasts to the Revised National Budget (RNB). In pForecast, a structure of RNB profiles and projects can be defined under the RNB tab.
Rs: Rs and GOR are used interchangeably.
Voidage factor: In pForecast, the voidage factor is a user input that means the same as Voidage Replacement Ratio (VRR). It is defined as follows:
Voidage group: Used to group producing wells and injector wells on the same reservoir in connection with Voidage Management. A specific voidage factor (VRR) will be assigned to each voidage group.
Volume-based profile: By turning on this toggle, the total volume of the production potential will be preserved even if there are limitations on the production. Such limitations could be production efficiency, shut-down periods, and potential reductions due to capacity limitations.
We help the petroleum industry generate the best possible forecasts for the most complex reservoirs. pForecast is a Software as a Service (SaaS) solution to digitalize, simplify, and standardize how production forecasts are generated and utilized. pForecast performs a full lifetime simulation of the production and injection forecast, including historical data, in keeping with the industry’s ever-increasing need for agility. Powersim Software is the software company and developers behind the pForecast solution.
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