Cross-Spectral Analysis for Inter-Well Connectivity Assessment
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Solution Overview
Problem
Current methods for determining inter-well connectivity in hydrocarbon reservoirs using permanent downhole pressure data are inefficient due to challenges in interpreting connectivity signals amidst noise and transient factors, requiring a fast and reliable technique for accurate reservoir characterization.
Innovation Solution
The method involves cross-spectral analysis of time series data from multiple wells to assess hydraulic connectivity by comparing spectral content, using techniques such as coherence and phase spectral analysis, and preprocessing steps like detrending, normalization, and spurious spike elimination to isolate meaningful connections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If visual comparison technique is used to determine inter-well connectivity, then the method is simple in theory, but it is difficult to apply in practice due to noise and transient factors affecting bottom hole pressures
Solution Approach 1:
The patent replaces the manual visual inspection method with an automated spectral analysis system. The system uses signal processing techniques (spectral coherence analysis) to automatically detect connectivity patterns in pressure data, eliminating the need for manual visual comparison and making the method both simple to implement and effective in practice.
2Measurement precision
If history matching technique is used to determine inter-well connectivity, then connectivity can be estimated, but the process is time consuming and non-unique
Solution Approach 1:
The patent extracts the essential connectivity information directly from the spectral coherence of pressure signals, bypassing the need for complete history matching. By focusing on the specific spectral characteristics that indicate connectivity, the method obtains accurate connectivity estimates without the time-consuming process of matching entire pressure histories.
Solution Approach 2:
The patent transforms the pressure time-series data into the frequency domain using spectral analysis. This parameter transformation allows connectivity to be assessed through spectral coherence metrics rather than through time-domain history matching, significantly reducing processing time while maintaining accuracy.
3Productivity
If spectral analysis method is used to determine inter-well connectivity, then rapid and accurate determination is achieved, but preprocessing steps are required to filter noise and eliminate spurious spikes
Solution Approach 1:
The patent applies preprocessing steps (detrending, normalization, spike elimination) before the main spectral analysis. By preparing the data in advance, the method ensures that the subsequent spectral coherence calculation is accurate and reliable, while the overall process remains efficient and automated.
Data Source
AI summary
Method for quantitatively assessing connectivity for well pairs at varying frequencies. A time series of measurements (12) is chosen for each of the two wells such that the particular measurements will be sensitive to subsurface connectivity if it exists (11). The two time series may then be pre-processed by resampling to time intervals commensurate with response time between the two wells (13), detrending the measurements (14), and detecting and eliminating spiking noises (15). Then the time series are transformed to the frequency domain where coherence and phase between the two series are compared for varying frequencies (16). This comparison is used to make a determination of connectivity.