Microseismic Velocity Models from Historical Classification
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Solution Overview
Problem
In seismic velocity modeling for hydrocarbon exploration, existing techniques face challenges in accurately locating microseismic events in subsurface formations with fractures, preferred grain orientations, and tectonic stress regimes, leading to complex seismic imaging and anisotropic characteristics, which require high accuracy in velocity modeling to adhere to geological, petrophysical, and geophysical properties.
Innovation Solution
The generation of optimized initial microseismic velocity models based on historical velocity models from nearby well sites, using a process that selects relevant well sites, obtains and correlates velocity components, performs non-linear regression, and refines the model with actual microseismic data to improve location accuracy and reduce processing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional seismic velocity modeling techniques are used for subsurface formations with fractures and anisotropic characteristics, then the velocity model accuracy is improved, but the processing time and computational complexity increase significantly
Solution Approach 1:
The system performs preliminary classification of historical velocity models into anisotropic and isotropic categories before actual velocity modeling. This pre-processing step allows the system to quickly determine whether simplified isotropic models or more complex anisotropic models should be used, reducing unnecessary computational overhead while maintaining accuracy when needed
Solution Approach 2:
The system dynamically adjusts the complexity of velocity modeling by changing the anisotropy parameter based on formation characteristics. When formations are determined to be isotropic or nearly isotropic, the system uses simplified velocity models with fewer parameters, thereby reducing processing time while maintaining sufficient accuracy for the given geological conditions
2Measurement precision
If complex anisotropic velocity models are used to accurately locate microseismic events in formations with preferred grain orientations and tectonic stress regimes, then the location accuracy is improved, but the device complexity and computational requirements increase
Solution Approach 1:
The system dynamically adapts the velocity model complexity based on the specific geological conditions being analyzed. Rather than always using complex anisotropic models, the system adjusts the modeling approach in real-time based on formation characteristics, making the system both accurate when needed and simple when conditions permit
Solution Approach 2:
The system introduces an intermediate classification step that acts as a mediator between the raw geological data and the velocity modeling process. This classification layer determines the appropriate level of model complexity, serving as an intelligent intermediary that prevents unnecessary computational complexity while ensuring accuracy when geological conditions require it
3Productivity
If historical velocity models from nearby well sites are used to generate initial models for new well sites, then the processing time is reduced, but the model accuracy may decrease due to geological variations between sites
Solution Approach 1:
The system implements feedback mechanisms where actual microseismic data from new well sites is used to validate and refine the transferred velocity models. The system continuously compares predicted event locations with actual observations and adjusts the model parameters accordingly, ensuring that historical data is used effectively without compromising accuracy
Solution Approach 2:
The system applies local adjustments to velocity models transferred from historical well sites, modifying parameters specific to the new well site's geological conditions. Rather than using a blanket transfer approach, the system preserves the useful general characteristics from historical models while allowing local customization to account for site-specific variations
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides more accurate estimates of microseismic event locations, reduces processing time, and enhances system performance for real-time microseismic applications by leveraging historical data to create a reliable starting point for seismic wave propagation simulations.
Implementation Method 1
seismic waves are propagated through an underground formation. The propagated waves are reflected through the formation and acquired using various seismic signal receiver devices
Implementation Method 2
Geophones run on wireline or fiber-optic cable in nearby offset wells can detect the sound waves emitted from these rock breaks
Data Source
AI summary
System and methods for generating microseismic velocity models are provided. One or more existing well sites in proximity to a planned well site are selected. Historical microseismic velocity models associated with the selected well sites are obtained. The formation depths for each velocity component of the historical models are correlated to formation depths from well logs acquired for a subsurface formation associated with the planned well site. A classification and non-linear regression on the historical microseismic velocity models is performed to identify the best-fitting velocity components for layers of the subsurface formation corresponding to the correlated formation depths. An initial microseismic velocity model of the formation is generated using the best-fitting velocity components. Seismic wave propagation through each layer of the formation is simulated using the generated model. Locations of one or more microseismic events of interest within the formation are estimated, based on the simulated wave propagation.