I had the pleasure of sitting through Dr. Mohamed Gabry’s presentation on CWT to analyze complex fracture networks using the water hammer response at shut-in, as part of NSI’s Wed(NSI)day technical presentations series. The concept of CWT is new to me, I’m more traditional in Fourier transforms, but I believe I understand the basics by using a wavelet that passes along the time-based water hammer dataset, matching the wavelet to the waveform to determine parameters. These damping parameters that would then generate a unique exponential decline curve which then defines the fracture network complexity. I am amazed at it was able to deconvolute the incredible complexity of multiple reflections and flowpaths, and seems like a good diagnostic tool which matches fracture density logging results (avoids a logging run in a debris-laden well!). However I missed how it could be used as a design tool currently, which I am equally interested in as an engineer. I would like to correlate the fracture complexity to parameters necessary for proppant transport and production, like fracture width and tortuosity, to understand how to improve subsequent treatments in our forward-looking design models.
From field experience in testing and measuring water hammer in Permian I learned:
- Rate, fluid volume, and modulus of elasticity of the flow path are important
- Speed of sound of the fluid must be calibrated correctly, such as adjusting for changing density, solids fraction, viscosity, and phase/flow regime
- Shut-in ideally is instantaneous without fluid loss (practical inside a cement wellbore, but in the formation…?)
- High data rate recording is necessary, I used perforating gauges to gather data points
- Pressure signals recorded at surface are a superposition of:
- Waves in pipe, with reflections from the sump and surface
- Waves reflected by restrictions (perfs, pinched fractures)
- Waves in the fractures propagating to the tip
- And heavily influenced by differential elements
- Tortuosity in the perforation tunnels creating time lag and discontinuity
- Friction in the fractures and choke points
- Leakoff (changes in reflected fluid volume) – high perm will have larger volumes lost
We were able to develop the water hammer and tweak it to match the response downhole, however I was fortunate to only need to measure the transient wave with incompressible fluids inside the pipe, with fixed values. Reflection throughout the wellbore was negligible as we were measuring the immediate hammer and decline at the perfs, with sump and surface far away. Decline was not critical for the experiments, whereas it is important in the CWT fracture network analysis. Even after thinking and writing this, I am still amazed at how it could analyze the superposition of pressure transients.
For any that are experienced in using fracture network diagnostics for production analysis and planning propped fractures, what value does this kind of analysis give you? Can simply knowing a fracture network complexity give you enough additional data, along with recorded field and pumped treatment data, to give accurate predictions? If you are experienced in CWT as an analysis tool, does the parametric curve fit help you to ultimately match physical parameters for the water hammer model?