Third Party Tools
Any structured geological model/gridding program may be
used with Sensor. Use of a third party Sensor-compatible preprocessor
allows direct import and processing of industry standard reservoir
descriptions without the need for any data reformatting.
Without a Sensor-compatible
preprocessor, inclusion of geo/grid model output in the Sensor
data file requires specification of the grid
dimensions using the GRID card, and replacing any geo/grid model array
labels with those accepted by Sensor. Any unit conversions that might
be needed can be made with simple array modifications in the Sensor data.
For faulted or corner point grid representations, the geo/grid model should provide
cell pore volumes, depths, and transmissibilities.
Any unstructured geo/grid model can also be used with Sensor if it can
provide pore volumes and transmissibilities in the context of neighbor and
non-neighbor connections in a structured grid.
Any phase behavior program can be used with Sensor.
For compositional cases, Sensor reads tabular component equation-of-state
properties with arbitrary column order.
PhazeComp is a state-of-the-art,
package for compositional phase behavior modeling and fluid
Pre- and Post-processing
By SANTEC, LLC
RExcel is a reservoir simulation pre-processor designed specifically for
the Reservoir Engineer. Within one work environment you can manage large
highly complex full field models or small mechanistic models. RExcel was
designed to empower the engineer and enhance creativity when configuring
Highly parallel code provides a robust environment when managing
multi-million cell models. Even on a laptop.
Import corner point reservoir descriptions from geological models like RMS
Easily model Hydraulically Fractured unconventional wells.
Combine data within a single project to define multiple models then simulate
Easily add Local Grid Refinement using any criteria to your model.
Quickly build Dual Porosity models with Single or Dual Permeability.
ProDrill Technology makes designing wellbores a simple task.
Aquifers may be configured along any boundary around a grid.
Full mathematical and advanced Modifier programming with Free Variables
provides unprecedented power and flexibility.
A built-in simulation Job Queue makes management of hardware resources easy.
Quick Build options enable engineers to build models in minutes.
Fully compatible with SENSOR.
By SANTEC, LLC
REView is a reservoir simulation post-processor that allow you to quickly
and accurately analyze simulation results.
Load and compare multiple simulation runs.
Analyze 3D maps, 2D maps and a wide variety of XY plots in multiple windows.
Generate a wide variety of images for technical papers, presentations or
other uses such as web pages.
Rank and quantify history matches from multiple runs.
The look-and-feel is identical to RExcel which makes the software easy to
Fully compatible with SENSOR and RExcel.
from Nitec LLC has powerful pre- and post- processing capabilities along
with numerous simulation input and output data analysis technologies. Some
of these technologies, such as HM “mismatch” maps, comparison of multiple HM
cases, polygon picking to create well groups, rigorous utilization of RFT
and PLT data, and natural fracture characterization using well logs and
multi-scale curvature analysis provide a powerful tool to assist the
engineer in the modeling process.
accelerates the model building and HM process and enhances the quality of:
simulation history match, and
The software’s single
database eliminates possible data transfer errors, provides a consistent
single source for data, and significantly reduces the amount of time
required to perform integrated studies.
It can handle multiple
characterization cases/multiple upscaled simulation grids (models) and
provide a comparison of results among them. It is a simulator pre- and post-
processor with the analysis tools needed to truly integrate all the data and
maintain consistency between the geologic model and the numerical simulation
Results Visualization and Analysis
Tecplot RS brings all your
reservoir simulation and observed data together, enabling you to rapidly
explore, compare, and understand your data.
With one tool,
Assess the accuracy of a reservoir model more quickly by comparing
history match factors for multiple simulation runs on a single plot.
Quickly identify regions of a reservoir with the largest history
Explore and analyze different well scenarios for forecasts.
Analyze and understand production data and simulation results in one
accurate, high-quality images for the web, presentations, and
Advanced workflows are
available around Sensor that promise to significantly improve productivity
and profitability through assisted history matching, optimization, and
uncertainty quantification. These can be generally described as
circular workflows with integrated Sensor pre- and post-processing
capabilities, and evaluation, optimization and run control algorithms.
A basic capability and a scalable benefit is the management of serial runs
on multiple CPUs to simultaneously evaluate multiple sensitivities.
"The first rule of any
technology used in a business is that automation applied to an efficient
operation will magnify the efficiency. The second is that automation
applied to an inefficient operation will magnify the inefficiency." -
automated Pipe-it workflows:
Deterministic Upscaling, and Deterministic or Probabilistic History Matching
Deterministic Predictive Optimization and Forecasting
Probabilistic Predictive Optimization and Forecasting
Probabilistic Alternative Optimization
workflows use our tools SensorPx / Makespx / MakeOptDat along with other
programs that are provided with Sensor.
is the latest innovative history matching (HM) technology from NITEC that is
very easy to use, fully utilizes available computing resources, and provides
fast, reliable HM solutions. MatchingPro only requires a reservoir
simulation model combined with historical production, injection, and
pressure data to accurately and efficiently determine the best HM solution
based on the selected HM parameters. No thinning of the historical data is
MatchingPro can function
in auto or manual modes to achieve a high quality HM solution. In the
MatchingPro auto mode, simulation cases are designed, run, and evaluated
without user intervention. The process is expedited by utilizing multiple
computer CPUs, when available.
edge technology makes use of Artificial Neural Networks (ANN), Genetic
Algorithms (GA), and statistical methods. These algorithms quickly reveal
the complex relationships among the HM parameters and the simulation results
(the mismatch in simulated versus historical volumes and pressures).
MatchingPro quantifies the quality of each HM case and determines the best
combination of HM parameters to achieve the best HM solution. MatchingPro
can also find multiple HM solutions (model characterizations) and provide a
quantification of their probabilities of occurrence.
MatchingPro can be used
with Sensor and other commercial simulators.
The MatchingPro Process: Auto Mode
The observed performance
data sets are easily loaded into MatchingPro. This includes: individual well
monthly production or injection volumes; static reservoir pressures from
build-up tests or shut in wells; and dynamic bottom hole pressures from
The HM parameters and
their associated physical ranges are defined via an interactive window. The
parameters can be continuous or discrete by defining them as real (linear or
logarithmic), or as integer.
In order to search for
the best solution (defined as a set of HM parameters) or multiple solutions,
an objective function is defined. The objective function weighs each
“mismatch variable” (oil, water, and gas production, injection, and
pressure) for use in the minimization calculations. The mismatch can be
minimized for selected wells, gathering centers, or the total field.
MatchingPro includes a default objective function that is applicable to most
situations. The objective function can be modified at any time during the
history matching exercise (auto or manual mode) and does not require
repeating of the simulation cases or regeneration of the correlation model.
MatchingPro commences a
pre-determined iterative process. Simulation cases are created, run,
analyzed, and displayed as each case is completed until the entire routine
is finished. Once all of the runs are executed, the final plot reveals the
best HM solution.
One of the unique
features of MatchingPro is the ability to generate multiple history match
solutions for the same HM problem. MatchingPro also calculates the
probability of occurrence of the set of HM parameters determined for each
acceptable HM solution. The minimized objective function value is typically
very similar for each solution. However, these different solutions may
result in very different performances in the prediction cases. This
highlights the well-known non-uniqueness of HM solutions.
Once the MatchingPro
process has completed and a satisfactory history match solution has been
found, as exhibited by a very low objective function value relative to other
simulation runs, the user can utilize MatchingPro’s solution clustering
algorithm to determine multiple HM solutions. These solutions may be equally
acceptable from the perspective of the objective function (overall HM
error), but will have different values for the individual HM parameters.
The user can utilize
MatchingPro’s Monte Carlo technology to sample the correlation model, say
one million times. From this sample, the user can request the number of
multiple HM solutions desired. MatchingPro’s clustering technology groups
these solutions accordingly and calculates the probability of occurrence for
Each of these solutions
will have different HM parameter values, but the objective function value
will be very similar indicating an equally acceptable solution.
While the HM parameter
values may appear similar, experience indicates that very minor differences
in the final HM parameters can result in significant variations in
A display of the
predicted performance for a well in a large field where three HM solutions
were generated shows the predicted performance for the same operating
scenario can be quite different for the three equally acceptable, HM
is an extension of the technologies encompassed in NITEC’s MatchingPro
software. It is designed to aid the user in developing optimal drilling
locations and schedules. The software utilizes all available computing
resources and provides flexibility to the user in defining and scheduling
the drilling program.
PlanningPro utilizes a
proprietary process to evaluate prospective new well locations, rank the new
wells based on cumulative oil, gas or BOE production potential and
determines the optimal combination )locations and timing) of new wells. The
technology developed in PlanningPro allows a minimal number of simulation
cases to be utilized to determine the optimal case. The process is
completely automated once the user specifies certain parameters.
currently be utilized with Sensor and other commercial simulators.
The PlanningPro Process
The prospective new
wells to be evaluated and scheduled are first imported or input to
PlanningPro. PlanningPro requires only the well name. The simulation data
deck (template file) must include these same wells and the typical well
information – I, J, K, PI, etc. The simulation deck should also include the
typical well, field, gathering center constraints, gathering center
identification, well types, etc. There is no limit to the number of
prospective new wells that can be input at this time. The user will later be
able to select the maximum number of wells to evaluate.
The drilling schedule
parameters must be input. These include days to drill each well, completion
days per well, number of drilling rigs available and the start date for
drilling. Simulation well types must be identified – Liquid producer, Oil
producer, Water injector, etc. This should be consistent with the simulation
data deck. The user will then define the maximum rate constraint for each of
the wells. PlanningPro will write the well rate constraints to the
simulation data deck.
Having defined the basic
well and simulation parameters, the user is asked to identify the actual new
wells to be evaluated. Typically, if the original list of wells input to
PlanningPro included 50 wells, all of these wells would be selected.
However, this need not be the case. The user can then define the objective
function to be based on cumulative oil, gas or BOE production. Economic
parameters can also be input in order to calculate a pseudo Net Present
Value for each case.
process first ranks all of the new wells to be evaluated. This is based on a
proprietary objective function. This ranking is then used to simulate the
model performance starting with the highest ranked well and adding each
additional new well through to the lowest ranked well according to the
drilling schedule parameters. The user can select all wells previously
identified to be evaluated or a lesser number from the ranked list.
The process of ranking
the wells is carried out with simulation runs of a relatively short
prediction period; shorter than the overall simulation prediction period
desired. Three to five years may be simulated in the ranking runs if the
full prediction period is 20 years. Once the ranking has been established
the full prediction runs are made.
As the process
progresses a bar chart is generated to display the objective function value
for each simulation case – ranking through scheduling cases. PlanningPro
reports the cases being processed and those waiting to process. If economic
parameters were input on the Objective Function screen, the “pseudo”
economic analysis, discounted net present value is displayed as a Black line
on each bar in the figure.
The resulting drilling
schedule can be displayed along with the production for each well.
PlanningPro allows the user to display production rate and cumulative plots
for any of the simulated cases and compare one case to another. Results can
also be exported to .csv files for use in other applications.
is the latest technology from NITEC for evaluation of uncertainty associated
with prediction case scenarios in reservoir simulation. ForecastingPro uses
defined uncertainties in reservoir and operating parameters and simulation
model runs to evaluate the probability of the performance results. The
results are displayed as rate and cumulative production and injection
profiles as a function of time for P10 through P90.
ForecastingPro utilizes proprietary technology to assess the impact on
forecasted field performance of an unlimited number of user defined
reservoir and operating parameters which are varied over user specified
ranges. The evaluation can be initiated at time zero (a Greenfield) or from
history match run results from MatchingPro with their associated
probabilities or from history match runs that have been made independent of
MatchingPro. The process is completely automated once the user specifies the
ForecastingPro can currently interface with the Sensor and other commercial
simulators. Only Eclipse currently allows changes to reservoir parameters on
a restart run.
ForecastingPro needs very little information about the particulars of the
prediction case or the reservoir being evaluated. Reservoir parameters and
well and field data are only provided in the simulation data deck and need
not be imported into ForecastingPro. The simulation data deck is treated as
a template file which contains the user defined variable names for the
uncertain parameters used in the analysis. These parameters must be
identified along with the range over which they can vary. If this is a
prediction study from an existing history match model, these parameters are
typically those which do not have an impact on the history match period, but
may have an impact on the predictions.
The user can identify a large number of uncertain reservoir and operating
parameters, but choose to vary only a few in the analysis; others can be set
to constant values. This provides the user with flexibility during the
ForecastingPro’s automated process uses distributed computing, hence it can
take advantage of cluster servers and multiple CPUs to speed processing of
the simulation runs required in the analysis. Once the user has identified
the uncertain parameters to use in the analysis, the software determines the
number of simulation runs that will be required to achieve reliable results.
For more than five variables, testing has indicated that the number of
simulation cases needed is 6 to 8 times the number of uncertain reservoir
parameters being evaluated. This is significantly fewer simulation runs than
required by other software that rely on Latin Hypercube search methods for
Proprietary technology is used to develop an accurate response surface of
the simulated field performance of oil, water, and gas production profiles,
as well as gas and water injection profiles. Initial experimental design
(scoping) runs are followed by a series of simulation (investigation) runs
that sequentially improve the ability of the response surface to predict
performance from any given set of uncertain parameters. By default, all
simulation prediction constraints are honored in all simulation runs, hence
the predicted performance is only impacted by the perturbed parameters.
Once the auto process has completed the user can view the difference between
the predicted performance of the response surface and the actual simulation
run results for each run in a simple bar chart.
this point the response surface has been calibrated to the actual simulation
runs. To assess the performance profile for any combination of parameters
and the associated probability, Monte Carlo analysis is used. The user can
select any combination of the parameters which have been varied or can
specify that some should have a specific value. The number of Monte Carlo
samples is input and the calculations are made. A sample of 50,000 has been
found to be generally satisfactory, but a larger sample can be specified.
This typically takes 30 seconds using a generic Windows personal computer.
Once the calculations have been made a cumulative performance profile (oil,
water, gas production and gas, water injection) is available for display.
P10 through P90 results are shown at 10 percent increments. Rate profiles
are also available.
The default frequency for the time interval used in the Monte Carlo analysis
is annual. However, the user can select less frequent time periods to speed
the analysis. Statistics in the form of distribution and Tornado charts can
be displayed if desired. The user can then evaluate the statistics
associated with any probability result at any of the specified times during
From Energy Scitech
creates and manages a multi-run environment, accelerating
history matches, bids,
appraisals or development plans,
giving confidence intervals
around predictions and identifying
globally optimal plans under
helps engineers to use a consistent workflow in all
simulation projects, whatever their business
objectives. Any aspect of the reservoir description
that is input to Sensor can be chosen for systematic
then makes a suite of runs in which the impact of every
parameter is investigated with maximum efficiency. The
results of the runs are presented to the engineer for
review. Using practical diagnostic tools in
it is very easy for engineers to focus in on aspects of
the reservoir performance that are important to the
project objectives and to steer the course of the
study. Understanding of the field and the model is
gained rapidly, leading to models that more closely
match requirements. Behind the scenes,
statistical framework ensures that all the runs made are
chosen efficiently, minimizing the number of runs. When
history matching, most projects take only 25% of the
engineering time needed to complete them using trial and
error techniques. Sensitivity or history match studies
lead on seamlessly into EnABLE-supported
optimization of development plans that makes use of the
results of runs already made.
MEPO, by SPT
is a step change in the reservoir engineering workflow. It
substantially enhances the value you will get from your existing reservoir
simulation models, by enabling a "multiple realisation" approach – allowing
you to not merely model your reservoir, but to optimise it for maximum
performance. MEPO can be used to improve your reservoir decisions in a
number of areas – from determining the best locations for infill wells, to
selecting the optimal development scenario, understanding uncertainty, or
semi-automating laborious tasks such as history matching. Best of all, it
works in harmony with almost all reservoir simulators including SENSOR, and
is simple to understand and use.