Wavelet Frequency Analysis of Long-term Transient Pressure from Permanent Down-Hole Gauges (PDG) for the Real-Time Reservoir Monitoring

Abstract

This paper describes a new method of analyzing long-term Permanent Down-hole Gauge (PDG) data for real-time reservoir monitoring. The wavelet frequency analysis approach developed can identify dynamic changes in reservoir properties and well conditions from PDG data.PDG is the down-hole measuring device installed during the well completion, and can provide continuous pressure, temperature and sometimes flow rate data. The real-time and long-term down-hole mentoring has been proved to be cost-effective through field applications.Analyzing the large quantity PDG pressure data and converting the data to economic value is challenging. Different from short time traditional well test, the long-term PDG pressure data records the dynamic change in reservoir properties and well condition with time, such as permeability and skin change due to formation damage, water breakthrough and gas out of solution. Diagnosing these dynamic changes and making immediate responses is the key for reservoir monitoring.Wavelet transform has been successfully applied in PDG data processing, such as data denoising, outlier removal and transient identification. This paper uses wavelet transform to reveal reservoir information by analyzing PDG transient pressure in frequency domain. Small rate change can lead to small transient pressure change and small frequency amplitude in frequency domain. For large rate change, the corresponding pressure change will cause large frequency amplitude. As studied, for the reservoir with constant properties, the frequency amplitude caused by unit rate change is constant with time. When there are properties changes, such as skin and permeability change, the frequency amplitude caused by unit rate change will change with time. According to this, a key diagnostic function has been developed and the dynamic changes in reservoir properties can be clearly identified.Synthetic cases and real field PDG data have been used to demonstrate that wavelet frequency analysis method can clearly identify the changes in reservoir properties, and realize the potential of PDG to provide more reservoir information. In detail, the significance of this method is shown as follows: 1) this method can identify production events and benefit production monitoring; 2) this method can identify nonlinearities caused by variable reservoir properties to reduce the uncertainties of pressure-transient analysis (for example, deconvolution only can be used in linear systems); 3) this method can identify timedependent reservoir properties and provide guidelines for reservoir model (near wellbore model) update.

Diagnosis of nonlinear reservoir behaviour for correctly applying the superposition principle and deconvolution

“…With pressure data processed with WT, there are amplitudes of WT coefficients at the time of transient events. Wang (2012) and Wang and Zheng (2013) quantitatively analysed the relationship between the amplitude of WT coefficients and the flow rate change, and an algorithm of calculating unknown flow rates was proposed. Wang and Zheng (2014) used WT to analyse PDG pressure data in the frequency domain to diagnose changes in reservoir properties.…”