Pre-and Post Stimulation Diagnostics using Spectral Noise Logging. Case Study.
- M. Volkov (TGT Oilfield Services UK ltd) | R. Ellis (TGT Oilfield Services UK ltd) | M Khabibullin (TGT Oilfield Services) | S. Uralsky (TGT Oilfield Services)
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- Society of Petroleum Engineers
- SPE Nigeria Annual International Conference and Exhibition, 6-8 August, Lagos, Nigeria
- Publication Date
- Document Type
- Conference Paper
- 2018. Society of Petroleum Engineers
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- 55 since 2007
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Tight or damaged reservoir sections often require stimulation to adequately perform. These sections can be identified as the well is drilled using LWD measurements and after drilling using open-hole wireline tools (RFTs, borehole imaging, and petrophysical logs). After the completion is run it is often impossible to make these measurements again, meaning that when sections are stimulated the only way to gauge stimulation effectivity is by measuring the change in flow rate within the completion, e.g. through a frac port. The physical reservoir response is not realized. Spectral Noise Logging can be used before and after each stage of a stimulation job to evaluate this response.
SNL distinguishes between matrix and fracture contribution (G. Galli, 2015) to flow allowing assessment of both hydraulic fracturing stimulation and acidizing. Acquiring behind pipe flow profile before the first stimulation stage will provide the baseline. SNL reservoir flow profile can be compared to open-hole logs (e.g. borehole imaging) and used to calibrate them with flow activity as the reference e.g. fractures identified from a formation imager can be seen and categorized as flowing or not flowing (Arthur Aslanyan, 2015). Logging SNL after the first stage of stimulation reveals how the reservoir responds, e.g. improved or new flow through existing fractures (comparing with borehole images), the appearance of new active fractures or change in matrix flow activity. If different stimulation strategies are implemented in the same well or reservoir, SNL can be used to assess and compare the effectiveness of each, resulting in the identification of an optimum stimulation technique.
How effective a stimulation job is largely dependant on the conformance of the completion of the job. If two zones have been targeted with some volume of a stimulation fluid, but a portion of this fluid leaks off to adjacent zones (e.g. through leaking packers) this will impact the degree to which the target zones react. Evaluating completion integrity is therefore crucial to understanding the effectiveness of a stimulation technique. Spectral Noise Logging is used to detect such leaks (Ihab Nabil Mohamed, 2012) making it integral to a wholistic approach in diagnosing stimulation effectivity. Furthermore, for many cases, well conditions render conventional PLT data useless (e.g. cross-flows dominate temperature profile, asphaltenes/solids affect spinner data) so noise data is the only measurement that can represent reservoir activity.
This paper will give such examples where SNL has been used to evaluate the effectiveness of stimulation jobs.
|File Size||2 MB||Number of Pages||18|
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