Data Blocking or Zoning: Well-Log-Data Application
- Nabil Al-Adani (Suncor Energy)
- Document ID
- Society of Petroleum Engineers
- Journal of Canadian Petroleum Technology
- Publication Date
- January 2012
- Document Type
- Journal Paper
- 66 - 73
- 2012. Society of Petroleum Engineers
- 5.8.5 Oil Sand, Oil Shale, Bitumen, 5.6.1 Open hole/cased hole log analysis, 2.4.3 Sand/Solids Control
- Facies, Zonnation, Auto Zone, Probabilities, Data Blocking
- 0 in the last 30 days
- 661 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 5.00|
|SPE Non-Member Price:||USD 35.00|
Several statistical techniques have been introduced in zoning sequential data such as well-log data or blocking experimental data. In general, these techniques lack the ability to optimize the predicted zones as per the desired number of blocks or zones. In addition, all these techniques' results depend on the amount of data inclusion in the blocking or zonation process. In this paper, a new method has been introduced to address the blocks or zones optimization and data-amount dependency. The new method also helps in establishing a new approach in estimating the data random error, if not known. This paper does not compare all techniques with the proposed approach. One technique has been selected to highlight the advantages of the proposed method.
An example of a Canadian oil-sand well has been used to demonstrate some applications of the new blocking or zoning method.
|File Size||5 MB||Number of Pages||8|
Agunwoke, G.O., Egbele, E., and Onyekonwu, M. 2004. A Statistical Approachto Reservoir Zonation. Paper SPE 88962 presented at the Nigeria AnnualInternational Conference and Exhibition, Abuja, Nigeria, 2-4 August. http://dx.doi.org/10.2118/88962-MS.
D'Windt, A. 2007. Reservoir Zonation And Permeability Estimation:A BayesianApproach. Paper 2007_UUU presented at the SPWLA Annual Logging Symposium,Austin, Texas, USA, 3-6 June.
Gill, D. 1970. Application of a Statistical Zonation Method to ReservoirEvaluation and Digitized Log Analysis. AAPG Bull. 54 (5):719-729. http://dx.doi.org/10.1306/5D25CA35-16C1-11D7-8645000102C1865D.
Lawal, K.A. and Onyekonwu, M.O. 2005. A Robust Approach to Flow UnitZonation. Paper SPE 98830 presented at the Nigeria Annual InternationalConference and Exhibition, Abuja, Nigeria, 1-3 August. http://dx.doi.org/10.2118/98830-MS.
Lee, S.H. and Datta-Gupta, A. 1999. Electrofacies Characterization andPermeability Predictions in Carbonate Reservoirs: Role of Multivariate Analysisand Nonparametric Regression. Paper SPE 56658 presented at the SPE AnnualTechnical Conference and Exhibition, Houston, 3-6 October. http://dx.doi.org/10.2118/56658-MS.
Levine, D.M., Ramsey, P.P., and Smidt, R.K. 2000. Applied Statistics forEngineers and Scientists: Using Microsoft Excel & Minitab. Upper SaddleRiver, New Jersey, USA: Prentice Hall.
Lim, J.-S., Kang, J.M., and Kim, J. 1997. Multivariate Statistical Analysisfor Automatic Electrofacies Determination from Well Log Measurements. Paper SPE38028 presented at the SPE Asia Pacific Oil and Gas Conference and Exhibition,Kuala Lumpur, 14-16 April. http://dx.doi.org/10.2118/38028-MS.
Souder, W.W. and Pickett, G.R. 1972. A Computerized Method for the Zonationof Digitized Well Logs. Paper SPE 4019 presented at the Fall Meeting of theSociety of Petroleum Engineers of AIME, San Antonio, Texas, USA, 8-11 October.http://dx.doi.org/10.2118/4019-MS.