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Collaborating Authors
Results
Enhanced Dispersion Analysis of Borehole Array Sonic Measurements With Amplitude and Phase Estimation Method
Li, Wei (China University of Petroleum-Beijing) | Guo, Rui (China University of Petroleum-Beijing) | Tao, Guo (China University of Petroleum-Beijing) | Wang, Hua (China University of Petroleum-Beijing) | Torres-Verdín, Carlos (The University of Texas at Austin) | Ma, Jun (The University of Texas at Austin) | Xu, Chicheng (The University of Texas at Austin)
Summary We introduce a new non-parametric matched-filterbank spectral estimator, referred as Amplitude and Phase Estimation (APES), to perform dispersion analysis of borehole array sonic measurements. This method extracts the dispersion characteristics of all wave modes by applying an APES filter to array sonic spectral data and converting the estimated wavenumber to slowness. The implemented adaptive filter in APES ensures that the output signal be sufficiently close to a sinusoid with a designated wavenumber in space domain, which constrains the interference from other wavenumber components and suppresses the noise gain. Consequently, the resolution and signal-noise-ratio of dispersion analysis is significantly enhanced. Dispersion fitness functions processed with APES indicate clearer and narrower ridges with minimum presence of alias. At each frequency, dispersions of all modes can be identified without knowledge a priori of the exact number of modes. More importantly, the new method is not computationally intensive compared to existing dispersion analysis methods. Processing examples with synthetic and field data are presented and compared with the weighted spectral semblance (WSS) method to demonstrate the applicability and advantages of this method.
Improved Estimation Of Pore Connectivity And Permeability In Deepwater Carbonates With The Construction Of Multi-Layer Static And Dynamic Petrophysical Models
Diniz-Ferreira, Elton Luiz (Schlumberger) | Torres-Verdín, Carlos (PETROBRAS – Petróleo Brasileiro S.A. and The University of Texas at Austin)
Due to sea-level variations, cycles of sedimentation can often be recognized from well logs. It is possible to differentiate rock types based on such geological cyclicity; for petrophysical purposes we will refer to those rock types as fluid flow units. In the presence of thin layers, flow units can only be detected with core data. The cause of sea-level variation in this field is not well understood and remains a subject of study by geologists. Wells were drilled with both oil-base mud (OBM) and water-base mud (WBM). The oil bearing-zone of wells drilled with WBM gave rise to a conspicuous invasion profile on resistivity logs. It is possible to simulate this invasion profile in different layers and estimate their permeability. Conversely, wells drilled with OBM did not show a conclusive invasion profile in the oilbearing zone because of the lack of electrical resistivity contrast between oil and mud filtrate. Due to the complexity of the pore space and the spatial heterogeneity of the reservoir under consideration, conventional well-log evaluation seldom reproduces petrophysical properties consistent with core data. It is necessary to construct multi-layer petrophysical models based on geological information to improve the interpretation. A model that combined well logs and geological properties was key to select bed boundaries and to construct an earth model. The latter model was used to perform static and dynamic simulations - matching simulated resistivity, nuclear, and NMR logs with field measurements. Petrophysical properties estimated with those simulations were in agreement with core laboratory measurements. Interpretation was performed in the oil-bearing zone of three wells: two of them-Wells Η and Γ – were drilled with OBM, the remaining well-Well Χ – drilled with WBM (Table 1). It is not possible to perform a correlation between the evaluated wells using well-logs.
- South America (0.93)
- North America > United States > Texas (0.29)
ABSTRACT: Nuclear magnetic resonance (NMR) is widely used to assess petrophysical and fluid properties of porous rocks. In the case of fluid typing, two-dimensional (2D) NMR interpretation techniques have advantages over conventional one-dimensional (1D) interpretation as they provide additional discriminatory information about saturating fluids. However, often there is ambiguity as to whether fluids appraised with NMR measurements are mobile or residual. In some instances, high vertical heterogeneity of rock properties (e.g. across thinlybedded formations) can make it difficult to separate NMR fluid signatures from those due to pore-size distributions and fluids. There are also cases where conventional fluid identification methods based on resistivity and nuclear logs indicate dominant presence of water while NMR measurements indicate presence of water, hydrocarbon, and mud filtrate. Depending on drilling mud being used, and the radial extent of mud-filtrate invasion, the NMR response of virgin reservoir fluids can be masked by that of mud filtrate. In order to separate those effects, it is important to reconcile NMR measurements with electrical and nuclear logs for improved assessment of porosity and mobile hydrocarbon saturation. We quantify the exact radial zone of response of NMR measurements and corresponding fluid saturations with studies of mud-filtrate invasion that honor resistivity and nuclear logs. Examples of application examine field data acquired in thinly-bedded gas formations of the Wamsutter basin invaded with water-base mud, wherein residual hydrocarbon saturation is relatively high. Additionally, fluid identification and partial porosity calculations obtained from a T1-T2 map indicate that NMR measurements originate from a radial annulus approximately 5 inches into the formation where the pore space is predominantly saturated with water but in which gas saturation is still higher than residual saturation. It was also found that the uncertainty of total NMR porosity could be as high as 3 pu because of noise and thin-bed effects.
- Geology > Rock Type > Sedimentary Rock (0.94)
- Geology > Geological Subdiscipline (0.88)
- North America > United States > Wyoming > Sand Wash Basin (0.99)
- North America > United States > Wyoming > Greater Green River Basin > Wamsutter Basin > Wamsutter Field (0.99)
- North America > United States > Wyoming > Greater Green River Basin > Almond Formation (0.99)
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