Saving cost with flexible pricing scheme
The i2G platform is affordable for various user types from independent consultants, small service companies to medium and large-size operators. Expensive workstation is not necessary anymore since user only needs one device to access the internet. Software as a service provides a very flexible pricing scheme from daily, monthly to yearly subscription. This scheme enables user to utilize the software for project on project basis which helps to avoid non-productive time and hence, reduce the overall cost.
Easily organize your messy and scattered project data
- Quickly filter project data by tagging
The data tree can be quickly filtered to display only needed data making it much more well-organized and hence easy to access. This feature saves a lot of time when user has to work with a huge project including many wells.
- Direct link between working project and related data
Within one unified working environment, the link between structured data that can be loaded into the working project and unstructured data such as well reports can be properly captured so that the time for data finding is significantly reduced. This hand-in-hand solution maximize the actual time working on the data rather than spending finding them. The user is also able to load data directly to the working project within the same environment/data storage project
- Comprehensive metadata system for quick data query
The data management system on i2G enables user to index and catalogue metadata or attributes related to well digital data as well as maps, core, rock, samples data and well reports. The system provides a full list of attributes/properties of any files uploaded. The user can also define their own metadata.
Benefits of using the i2G data query tool:
- Efficient search & retrieval capability, search for metadata related to physical as well as electronic E&P data efficiently
- Ability to save desired search for initiating the data query process
- Use different search criteria to look for the required data
Intuitively visualize and create your petrophysical workflow
- Interactive workflow creation and configuration
All tasks are easily saved to one or more petrophysical workflow. They can be reused later to run for other wells or to create a new workflow. With the ability to visually configure various calculation blocks including connect/disconnect, rearrange and disable/enable, users can customize their workflows in significantly less time.
- Multi-well multi-zone workflow execution
The available workflow can be applied for multi-zone and multi-well in a consistent manner. When it comes dealing with a huge project including many wells, the results are quickly generated and are comparable between wells.
Manage all frequently-reuse parameters and templates in one place for quickly retrieving and reusing
This can be viewed as a centralized asset manager to capture all fragmented assets produced during data pre-processing and interpretation. They contain Task’s Parameter Set, Workflow Template, Log-plot Template, User Defined Lines, Depth Shift table, Baseline Shift table, Split Curve table, Palette, Plot models and Zone Set backup from Workflow. One of the key advantages of the i2G asset manager is that Users can quickly load and propagate these existing parameters to the new workflow at zone, well, or project level.
Zone and marker template control system allows a consistent display and fast creation
- Easy to set up a correlation
On available multi-well logplot, i2G supports displaying zone set/market set quickly by selecting them on properties editor window. This also makes switching between different zone set/marker set easier than ever.
- Flexible in adding new zone/marker and/or modifying the current ones
New zone/marker can be simply added interactively on the logplot or by assigning the top and bottom depths for the zone. I2G offers the ability to split a zone into different smaller zones and assigned other pre-defined templates.
- Template control system allows consistent display
The display of zones/markets that have the same template are consistent across all wells. When users modify template style such as color, line type and name, all zones/markers associated with the templates are automatically updated as well.
Intuitively predicting data using most popular machine learning algorithms, no coding needed
- Robust workflow implemented by machine learning experts
The workflow offered by i2G begins with input data selection, then model building and finally model validation. I2G provides various tools for analyzing data to select right inputs for building the model. During the model building step, users are able to filter the selected input curves to eliminate unwanted data samples such as in wash-out intervals. There are a number of plots that can help users to evaluate their machine leaning models, including train-loss crossplot, train-accuracy crossplot, confusion matrix and validation logplot. By using them, users are able to visually assess the model built and then make decision on how to improve the model.
- Various machine learning methods to deal with different geological complexities
I2G supports both regression and classification methods ranging from Decision Tree to Artificial Neural Network.
Here is the list of supporting classification methods:
- Decision Tree Classification
- KNN Classification
- Logistic Classification
- Neural Network Classification
- Random Forest Classification
Here is the list of supporting regression methods:
- Decision Tree Regression
- Huber Regression
- Lasso Regression
- Linear Regression
- Neural Network Regression
- Random Forest Regression
- SVM Regression
- Xgboost Regression
Besides, non-linear regression method and and Self-Organizing Map (SOM) are also supported. This is a nonlinear approach to model the relationship between the input curves and the target curve. The relationships are modeled using nonlinear predictor functions, so called nonlinear models, whose unknown model parameters are estimated from the data. Self-organizing Map is a unique tool for facies classification by both supervised and unsupervised modes. The tool provides a robust workflow from model construction to model validation which is critical to make sure the output brings actual geological meaning. Emsemble Boosting SOM and Distributed Ensemble SOM algorithms are also two supported algorithms which provides more options to deal with a wide range of geological complexities.
- Flexibility in configuring model inputs and architectures
I2G machine learning toolkit is open for user to adjust many advanced parameters such that the user has full control on model configuration. This is to avoid using i2G as a “black box”. For the user who is new to machine learning, default parameters are set to have reasonably good values to start with.
An AI system which can predict depositional facies. Save both cost and time for an equivalent quality
- Data-driven, re-producible and consistent results throughout an entire field
Most interpretations are largely subjective because they are based primarily on well logs, which are non-diagnostic for facies interpretation, integrated with minimal core data. However, a new hybrid approach which combines machine learning and an expert system generates data-driven, reproducible and consistent results for facies prediction across an entire field, which significantly reduces uncertainties when building a conceptual model derived from facies distribution.
- Able to deal with a huge dataset including many wells
One of the greatest challenges for depofacies interpreters is that they normally have to work on many wells in the same field. Depofacies predictor on i2G is basically done by the computer so they can work with hundreds of well simultaneously which can save a significant amount of time.
- Compensates for insufficient data for depositional environment interpretation
Unlike most machine learning models, the prediction is made considering data samples in the context of depositional units. First, the Gamma Ray curve is divided into different depositional units by tracking Gamma Ray value changes. The machine then automatically assigns to each depositional unit a Gamma Ray shape, lithofacies, boundary type and its stacking pattern with adjacent units. These parameters are integrated with a machine learning model built on core data from the studied basin plus any relevant biostratigraphic and then passed through an expert system containing a set of fuzzy rules to yield final probabilities curves for each of depositional facies. The facies above and below each unit, along with the style of each unit boundary, and their associated facies, are determined by looping back through the expert system after making the initial facies assignments, which produces a coherent stratigraphic succession. Outputs include predictions of the three most likely depositional facies for each unit and their respective probabilities.
Process thousands of wells with advanced calculations using Python
- Saving time for large projects by batch processing capacity
Users have the ability to do batch processing of any pre-defined workflow built from key wells. This has an advantage of saving a lot of time for interpreters since they now do not have to execute the petrophysical workflow well by well.
- Quickly deploy any advanced solutions with built-in python library
I2G supports most commonly used libraries such as Numpy, Scipy and Matplotlib. These libraries help user to accomplish various aspects of programming activities from simple to complicated calculations and database implementations
- Simple coding for non-programmer like geoscientists with multiple APIs supported
Python is a powerful multi-purpose programming language. With 100+ APIs, user can quickly implement their algorithms/workflow in significantly less time. Its simple and easy-to-use syntax makes it perfect for non-programmer like geoscientists.
Build-in chat support for instant communication
Platform such as i2G provide an integrated live chat so that users can communicate while working within the same environment. The advantage of this is interpreters do not have to go through thousands of emails to find information. All communications and evidence to support any decision and model/parameters selections are properly captured and attached to the project. This tool enables easy online supports and expert on call from Revotech G&G team.