A HEOLOGIC COMPANY
WE GUIDE CUSTOMERS IN SELECTING THE BEST POSSIBLE FIELD DEVELOPMENT DECISIONS TO INCREASE THE DAILY OR CUMULATIVE OIL PRODUCTION
A game changing solution that is revolutionizing the oil industry by improving oil production efficiency, reducing risks and cost of field development.
Froswell Simulator has been assisting various leading international organizations disruptively changing the paradigm of the O&G upstream industry, significantly increasing oil production and reducing water cut.
Our unique approach includes integration of heliometric data, modern physical models and powerful artificial intelligence to upgrade geological field models, assess the production potential of oil wells and select the most effective well interventions and water flooding optimization activities with highest possible result forecast accuracy.
Step I.
Well potential assessment
Maximum Possible Production Rate
Poorly Depleted Zones
Unpromising Producers (Potential Injectors)
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Helium constantly migrates vertically from crystalline basement through the sedimentary cover, forming microseepages at the earth’s surface.
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While migrating to the earth surface Helium can be temporary captured and accumulated in Helium traps – specific geological structures of enhanced Helium capacity.
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Oil and gas pools are efficient Helium traps due to significantly higher He solubility in hydrocarbons compared to formation water and surrounding dry fractures.
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After reaching saturation limit traps start releasing high Helium concentrations which migrate to the surface.
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The well is a perfect «migration path» for helium from reservoir to the surface.
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Helium wellhead study is carried out for registering actual helium concentrations at producing wells and identification of the well production potential.
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Wells with hydrocarbon production potential show high Helium concentrations.
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A high scatter and dispersion of Helium concentrations called “Helium arrhythmia” characterizes wells with unstable or low oil production advising certain well stimulations.
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Heliometric data at the wellhead is a multifactorial variable and depends on the production volumes, operational settings of the pump, depth of the object, the lithology, reservoir properties, the number of layers in the section, etc.
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Annually recorded Heliometric data tracks the dynamics of changes in producing/depleted/suspended deposits.
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Repeated measurement of Helium Gas at Wellhead
Repeated (min. 5 cycles) helium gas phase measurement in annulus across the oil field allows to identify the well production potential based on helium concentrations, prioritize producers for well interventions or switch them to injectors (in case of lack of hydrocarbon production capacity) .
Heliometric data is very insightful regardless of viscosity.
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Historical Well and Reservoir Data Compilation
We construct a unique field database adding all available cumulative reservoir information, historical well parameters and heliometric data obtained at the wellheads.
We sort a large amount (Terabytes) of information, 80% of which have never been used before. At this stage we identify high geological uncertainties of interdependent parameters.
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Field Express-Analysis for Potential Assessment
When conducting large field studies, we perform a quick analysis of all acquired data with machine learning to select wells suitable for the simulator, excluding some wells that can be managed manually as before.
At this stage low quality data will be verified and recovered, missing parts of information will be prepared for generation.
Step II.
Field Simulation
History Data Matching
Generation of thousands of adaptations
Initial Model History Matching
Automatic filtering and independent verification by machine learning of accumulated historical data ensures that the foundations of our work are solid.
Froswell's high-accuracy approach is based on data-driven physical models and machine learning algorithms that place wells, near-wellbore zones and interwell areas into shaped 3D cells with a confirmation of obtained models with physical measurement of heliometric data.
3D cell simulation approach greatly reduces the calculation time and makes it possible to implement automated history matching with hundreds, thousands of adaptation options in a matter of minutes or hours, while reducing to 20% the mean average per cent of error (MAPE). For comparison, traditional hydrodynamic simulators usually have an error from 100% to 300%.
The techniques used allow assessment of reservoir pressure, transmissibility at well connection, volumes of interwell areas, water saturation and distribution of oil saturated thicknesses at any historical moment, giving an accurate current state of field parameters.
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Data Matching with
Machine Learning
Froswell actively uses machine learning algorithms in working with historical well data to clean noisy data from the error of the measurements and improve data quality.
By filtering Initial data before loading it into simulator we revalidate all measurements over decades of field development. So dataset has minimum possible mistake.
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Field Simulation with physical model
Processed initial information is used to create physical and hydrodynamic field models based on material balance.
As a result, we get a fundamentally better picture: mutual influence of wells, the distribution of production and injection by reservoirs, the dynamics of reservoir pressure, maps of residual oil-saturated layers.
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Model History Matching
with Machine Learning
We use special techniques and algorithms to improve the calibration and matching of simulation models to historical data. It involves training models on observed data and simulation outputs to learn the relationship between input parameters and model responses, enabling more accurate and efficient history matching and selecting models close to real-world data.
Step III.
Model verification and by-passed oil
Confirmaton of By-passed Oil Locations
Selection of a model with the lowest error
Drilling De-risking
Froswell simulator generates virtual nodes (wells) that are used to analyze and predict the performance of the reservoir, understand fluid flow patterns and define geometry, production rates, water cut and interconnectivity with neighbouring nodes (wells). Each field model accommodates millions of virtual nodes.
To enhance the alignment of simulation models with real-world data and verify the most accurate model with the lowest possible mistake, we utilize advanced express-method of Areal Helium Surveying over the most remarkable virtual nodes generated by Froswell Simulator.
Collection of heliometric data is carried out by Advanced Heologic Field Systems at the dense grid in the most attention-grabbing virtual nodes that may have a significant impact on selection of the right field model.
Identified and integrated heliometric anomalies serve us as a Direct Hydrocarbon Indication (DHI), confirm saturation of by-passed oil, de-risk drilling locations, leading to improved model accuracy and reliability.
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This technique is widely used by Froswell in the early stages of field development and during EOR programs.
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Identification of the Most Remarkable Virtual Nodes
The Simulator independently selects the most critical virtual nodes to validate them by heliometric data.
Every selected virtual node has it's own impact to the model accuracy and considered as a potential location of by-passed oil with forecasted production rates and defined reservoir parameters.
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Virtual Nodes Confirmation with Heliometirc data
Areal Helium Survey designed to cover selected virtual nodes locations and confirm or refute by-passed oil saturation at the virtual nodes.
Helium anomaly maps produced on the basis of obtained Heliometric data. Helium anomalies ranked and digitalized in special dataset for Simulator processing.
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Field Model Confirmation for subsequent Simulation
At the moment of virtual node confirmation or refutation dozens of field models are calibrated and the most genuine model would be selected.
The authentic model is an accurate representation of the reservoir and accounts for uncertainties ensuring it reproduces realistic, reliable and justifiable assumptions.
Step IV.
Field Management Recommendations
Optimal Operation Producer Well Modes in connection to surrounding wells
Water Flooding Optimization Program
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Well Interventions with forecasted result
Receiving a more accurate physical model of the field solves the main production and water optimization problem allowing to automatically calculate hundreds and thousands of scenarios for the field development and drilling new wells.
By using the experience of previous well intervention and water flooding optimization activities Froswell predicts the dynamics of deposit development parameters under various impact scenarios and selects the best recommendations on what exactly should be done in the field (well intervention, changing well parameters, new drilling etc.) to maintain and increase production taking into account the existing surface infrastructure.
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Simulator is monthly updated with the data of accomplished field development activities and production results. Recommendations are generated monthly according to set goals and availability of budget and service teams.
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Assessment of Previous Field Activities
Before drawing up a field activity program we run Machine Learning module feeding data from previous well intervention, water optimization activities, and physical-hydrodynamic field model.
Simulator generates a strong realistic correlation between past field activities and achieved historical results ensuring true efficiency of available field development activities.
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Generating a List of Well Interventions and Water Optimization activities
A field activity plan generated by Simulator determines reasons of previous oil production losses, suggests optimal operating modes for injectors and producers, selects well candidates for well interventions (geological and technical), forecasts working parameters, calculates the waterflooding scenarios including a relatively simple changes in the parameters of group of wells.
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Model Constant Update based on Achieved Results
Our service includes drawing up and continually updating the field development plan with a list of well interventions and waterflooding optimization activities.
At any moment of time, our customers know what needs to be done at the field – what specific activities and when to carry them out in order to produce more oil and reduce watercut.