Time-Lapse Seismic Analysis for Rock Property Prediction
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Solution Overview
Problem
Current seismic analysis techniques for subsurface rock formations often face challenges with inaccurate, incomplete, or unavailable seismic data, which hinders the integration of field data into reservoir models, affecting hydrocarbon exploration and production.
Innovation Solution
The method involves acquiring and processing time-lapse seismic data to estimate time-dependent rock properties over multiple intervals, using seismic inversion datasets to predict future rock properties and simulate fluid flow, thereby enhancing the accuracy of reservoir modeling and fluid displacement analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional seismic analysis techniques are used, then the process is simpler, but the prediction accuracy of rock properties deteriorates due to inaccurate, incomplete, or unavailable seismic data
Solution Approach 1:
The method performs preliminary actions by acquiring seismic data at multiple time intervals (t1, t2, ..., tn) before the target future time point. This allows the system to establish trends and spatio-temporal relationships in advance, enabling more accurate predictions at the target time even when direct seismic measurements are unavailable or inaccurate at that specific time point.
Solution Approach 2:
The system uses feedback by comparing seismic data from multiple time intervals and using the observed trends and relationships to continuously improve predictions. The method incorporates feedback loops where predicted rock properties are validated against available seismic data, and the model is refined iteratively to enhance prediction accuracy for future time points.
2Measurement precision
If more seismic data is collected over multiple time intervals, then prediction accuracy improves, but the complexity of data processing and analysis increases
Solution Approach 1:
The complex task of analyzing seismic data across multiple time intervals is segmented into distinct processing steps: acquiring seismic data at each time interval, calculating rock property values for each interval, determining trends between intervals, and finally predicting future rock properties. This segmentation makes the overall complex process more manageable and systematic.
Solution Approach 2:
The method transitions from analyzing static seismic data to analyzing dynamic spatio-temporal relationships by adding the time dimension. By examining how rock properties evolve across multiple time intervals and identifying spatio-temporal patterns, the system extracts additional informative dimensions that improve prediction accuracy while providing a structured framework for handling the increased data complexity.
3Measurement precision
If seismic data is acquired at multiple time intervals, then time-dependent rock properties can be predicted, but the time and resources required for data acquisition increase
Solution Approach 1:
The method applies partial action by acquiring seismic data at select time intervals rather than continuously. By strategically choosing multiple discrete time points (t1, t2, ..., tn) that capture the essential evolution of rock properties, the system achieves sufficient prediction accuracy without the excessive time and resource cost of continuous monitoring. The trend analysis between these partial measurements enables inference of intermediate states.
Data Source
AI summary
System and methods for predicting time-dependent rock properties are provided. Seismic data for a subsurface formation is acquired over a plurality of time intervals. A value of at least one rock property of the subsurface formation is calculated for each of the plurality of time intervals, based on the corresponding seismic data acquired for that time interval. At least one of a trend or a spatio-temporal relationship in the seismic data is determined based on the value of the at least one rock property calculated for each time interval. A value of the at least one rock property is estimated for a future time interval, based on the determination. The estimated value of the at least one rock property is used to select a location for a wellbore to be drilled within the subsurface formation. The wellbore is then drilled at the selected location.