Multi-Layer Formation Pressure Determination by Triple-Rate Spectral Noise Logging and Data Verification by Transposed Pressure Deconvolution
- V. Taipova (PJSC Tatneft) | R. Zabbarov (PJSC Tatneft) | A. Chirkunov (PJSC Tatneft) | A. Aslanyan (TGT Oilfield Services) | I. Aslanyan (TGT Oilfield Services) | R. Minakhmetova (TGT Oilfield Services) | M. Garnyshev (TGT Oilfield Services) | R. Farakhova (Sofoil) | L. Surmasheva (Sofoil)
- Document ID
- Society of Petroleum Engineers
- SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition, 17-19 October , Jakarta, Indonesia
- Publication Date
- Document Type
- Conference Paper
- 2017. Society of Petroleum Engineers
- 5.6 Formation Evaluation & Management, 3 Production and Well Operations, 5.5 Reservoir Simulation, 3.3 Well & Reservoir Surveillance and Monitoring, 4.1 Processing Systems and Design, 5.6.3 Pressure Transient Testing, 4 Facilities Design, Construction and Operation, 5 Reservoir Desciption & Dynamics, 4.1.2 Separation and Treating, 3.3.1 Production Logging
- multi-layer formations, spectral noise logging, behind-casing communications, deconvolution, layer formation pressure
- 2 in the last 30 days
- 102 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 9.50|
|SPE Non-Member Price:||USD 28.00|
This paper aims to describe the technique of formation pressure determination in an active dual-zone injector. The calculated data have been compared with the formation pressures resulting from pressure transient tests conducted during production logging survey, and with dual-zone thermohydrodynamic modelling data.
The formation pressure determination method is based on high-definition broadband spectral noise logging (SNL) data analysis. It is known that the noise power produced by fluid flow as it propagates through the reservoir depends on differential pressure. The Triple-rate SNL technique can be used for formation pressure estimation in each hydrodynamically isolated reservoir unit by recording a noise profile across each flow zone at three rates. Wavelet thresholding and coherency filters are used to separate the component related to the reservoir flow from the total noise spectrum. The formation pressure in each reservoir unit was determined using PolyGon™ software package which aumonatically varies the skin- factor and formation pressure to fit the recorded noise response to recorded wellbore pressure at three rates simulataneously.
The survey targets described in this paper are terrigenous formations of Romashkino Field situated in the European part of Russia. Two major reservoir units commingled in one production target, although they are separated by an impermeable shale streak, can be distinguished across the reservoir section under consideration. Both units have similar reservoir properties.
An integrated survey including Spectral Noise Logging and High-Precision Temperature Logging tools was run in the well at three different injection rates in order to determine formation pressure in each injection layer. The recorded noise power increases in each layer as the differential pressure grows higher.
As a result of combined bottomhole pressure and noise power simulation, formation pressure was estimated for each flow zone of the reservoir units with pressure in the upper unit being 0.80 MPa higher than in the lower unit. This pressure difference is the cause of a crossflow in shut-in well, which was confirmed qualitatively by temperature surveys and then the crossflow rate was quantified through numerical simulations of temperature curves. The crossflow rate was low and therefore it could not be identified by means of standard PLT or even noise logging.
An analysis of pressure data recorded in the wellbore during the entire HPT/SNL-HD survey and then recalculated to the reference depth provided information on average reservoir parameters. The average formation pressure was determined using two techniques: pressure fall-off and deconvolution. A reliable correlation was obtained between average formation pressures derived from the pressure transient analysis, both PTA and deconvolution, and average weighted wellbore pressure according to the pressure profile determined by Triple-rate SNL.
This method of pressure evaluation in a cased injector is cost-efficient because in this case the wells do not have to be shut in for an extended period of time or downhole pumps pulled out.
|File Size||9 MB||Number of Pages||16|
Suarez, N., Otubaga, A., Mehrotra, N., Aslanyan, A.. 2013. Complementing Production Logging with Spectral Noise Analysis to Improve Reservoir Characterisation and Surveillance. Presented at the SPWLA 54th Annual Logging Symposium, 22-26 June, New Orleans, Louisiana. SPWLA-2013-TTT. https://www.onepetro.org/conference-paper/SPWLA-2013-TTT
Maslennikova, Y. S., Bochkarev, V. V., Savinkov, A. V., Davydov, D. A. 2012. Spectral Noise Logging Data Processing Technology. Presented at the SPE Russian Oil and Gas Exploration and Production Technical Conference and Exhibition, 16-18 October, Moscow, Russia. doi:10.2118/162081-MS. https://www.onepetro.org/conference-paper/SPE-162081-MS
Ghalem, S., Serry, A. M., Al-felasi Ali. 2012. Innovative Logging Tool Using Noise Log and High Precision Temperature Help to Diagnoses Complex Problems. Presented at the Abu Dhabi International Petroleum Conference and Exhibition, 11-14 November, Abu Dhabi, UAE. doi:10.2118/161712-MS. https://www.onepetro.org/conference-paper/SPE-161712-MS
McKinley, R. M., Bower, F. M., Rumble, R. C. 1973. The Structure and Interpretation of Noise from Flow Behind Cemented Casing. Society of Petroleum Engineers. doi:10.2118/3999-PA. https://www.onepetro.org/journal-paper/SPE-3999-PA
Aslanyan, A., Wilson, M., Al Shammakhy, A., Aristov, S. 2013. Evaluating Injection Performance with High-precision Temperature Logging and Numerical Temperature Modelling. Presented at the SPE Reservoir Characterization and Simulation Conference and Exhibition, 1618 September, Abu Dhabi, UAE. doi:10.2118/166007-MS. https://www.onepetro.org/conference-paper/SPE-166007-MS
Sarsekov, A., Al Neaimi, A., Abed, A.. 2016. Formation Pressure Evaluation for Producing Wells Without Shutting Down the Well, Using Triple Spectral Noise Logging TSNL. Presented at the Abu Dhabi International Petroleum Exhibition & Conference, 7-10 November, Abu Dhabi, UAE. doi:10.2118/182856-MS. https://www.onepetro.org/conference-paper/SPE-182856-MS
Eldaoushy, A. S., Al-Ajmi, M., Al-Shammari, M.. 2015. Quantification of Reservoir Pressure in Multi-Zone Well under Flowing Conditions Using Spectral Noise Logging Technique, Zubair Reservoir, Raudhatain Field, North Kuwait. Presented at the Abu Dhabi International Petroleum Exhibition and Conference, 9-12 November, Abu Dhabi, UAE. doi:10.2118/177620-MS. https://www.onepetro.org/conference-paper/SPE-177620-MS
Aslanyan, A., Aslanyan, I., Demski, C., Al Touqi, M. 2007. Evaluation of Water Flooding Efficiency Through the Static High Precision Temperature Logging. Presented at the SPWLA Middle East Regional Symposium, 15-19 April, Abu Dhabi, UAE. SPWLA-MERS-2007-I. https://www.onepetro.org/conference-paper/SPWLA-MERS-2007-I
Von Schroeter, T., Hollaender, F., Gringarten, A. C. 2004. Deconvolution of Well-Test Data as a Nonlinear Total Least-Squares Problem. Society of Petroleum Engineers. doi:10.2118/77688-PA. https://www.onepetro.org/journal-paper/SPE-77688-PA
Levitan, M. M. 2007. Deconvolution of Multiwell Test Data. Society of Petroleum Engineers. doi:10.2118/102484-PA. https://www.onepetro.org/journal-paper/SPE-102484-PA
Levitan, M. M., Crawford, G. E., Hardwick, A. 2006. Practical Considerations for Pressure-Rate Deconvolution of Well Test Data. Society of Petroleum Engineers. doi:10.2118/90680-PA. https://www.onepetro.org/journal-paper/SPE-90680-PA