Zhao, Tianhong (Southwest Petroleum University) | Chen, Ying (Southwest Petroleum University) | Pu, Wanfen (Southwest Petroleum University) | Wei, Bing (Southwest Petroleum University) | He, Yi (Southwest Petroleum University) | Zhang, Yiwen (Southwest Petroleum University)
Nanofluid flooding injection technique whereby nanomaterial or nanocomposite fluids for enhanced oil recovery (EOR) have garnered attention. Although a variety of nanomaterials have been used as EOR agents, there are still some defects such as toxicity, high cost and low-efficiency displacement, which restricted the further application of these nanoparticles. Considering these problems mentioned above, it is necessary to search for another nanomaterial which is inexpensive, environmentally friendly and results in high efficiency displacement.
In this work, a natural aluminosilicate nanomaterial halloysite nanotubes (HNTs) was focused. As a new kind of nanomaterial, the effectiveness of halloysite nanotubes (HNTs) in enhancing oil recovery has not been reported yet and it is still in its infancy. The use of pristine halloysite nanotube is at risk of blocking the rock pore channel due to the intrinsic drawback of aggregation, which may be the reason. To prolong the suspension time of fluids during seeping into the small pores of low permeable reservoirs, we have proposed the HNTs/SiO2 nanocomposites. The effect of HNTs/SiO2 nanocomposites-based nanofluids on wettability alteration and oil displacement efficiency was experimentally studied. The HNTs/SiO2 nanocomposites have been prepared by sol-gel method and characterized with X-ray (XRD), Transmission Electron Microscopy (TEM) and Thermal Gravimetric Analysis (TGA). The effect of the chemical modification on the suspension stability was investigated by measuring Zeta potential and dynamic laser scattering. Results show that the HNTs/SiO2 nanofluid could significantly change the water wettability from oil-wet to water-wet condition and enhance oil production. The optimal concentration of HNTs/SiO2 was 500 ppm, which corresponded to the highest ultimate oil recovery of 39%.
Hung, Barry (CGG) | Wang, Xusong (CGG) | Phan, Ying Peng (CGG) | Alai, Riaz (PETRONAS Carigali Sdn. Bhd) | Xin, Kefeng (CGG) | He, Yi (CGG) | Rahman, Nurul Nadzirah (PETRONAS Carigali Sdn. Bhd) | Tang, Wai Hoong (PETRONAS Carigali Sdn. Bhd)
Recent efforts in marine broadband processing have largely been focused on source and receiver deghosting. To fully recover the frequency bandwidth of seismic data, the anelastic nature of the earth needs to be taken into account. In addition, in the presence of gas anomalies, attenuation of seismic waves will cause further degradation in the resolution of migrated images. By quantifying the attenuation of seismic energy using quality factor Q, we can model the intrinsic absorptive nature of the earth as background Q and the localized absorptive bodies, e.g. gas pockets, as anomalous Q. Using the frequency information and the amplitude information of the data to estimate the background Q (FS-QTomo) and anomalous Q (A-QTomo), respectively, the attenuation effects of the earth can be compensated by the application of Q-PSDM in the presence of gas with the resultant combined Q model. The accuracy of these processes is further enhanced by broadband processing with deghosting in terms of better estimation of the centroid frequency for FS-QTomo and deeper penetration of low frequency signal through the gas bodies for A-QTomo. Thus, the interplay of deghosting and Q tomography provides a full broadband processing workflow for restoring the distortion of amplitude, frequency and phase caused by the combined effects of the earth’s anelasticity and gas pockets. We applied our workflow on a field data example and demonstrated through this first case study that high resolution broadband seismic data with improved signal to noise ratio (S/N) can be obtained.
Extending the usable frequency through broadband acquisition and processing has proven to be beneficial in the application of FWI (Ratcliffe et al., 2013), the enhancement of imaging (Zhou et al., 2014), studies of inversion (Soubaras et al., 2012), etc. In the area of broadband processing, one of the key steps is deghosting. In recent years active research has been conducted into both pre-migration and post-migration deghosting algorithms, as well as its application to different marine acquisition configurations, e.g. conventional shallow cable, variable-depth cable, multi-component cable etc.. For full broadband processing, however, the attenuation effects of the earth’s subsurface need to be taken into account. To this end, the intrinsic anelastic nature of the earth must be considered in the processing workflow. Moreover, in the presence of gas, both as shallow pockets and as commercial reservoirs (not an uncommon geological setting in many parts of the world), localized strong absorption from these gas bodies will cause amplitude dimming and frequency dependent dissipation, and this degradation in signal needs to be recovered.
The propagation of seismic waves through visco-acoustic media is affected by frequency dependent absorption which is often described by the quality factor Q where a low Q means more loss of signal strength and bandwidth. Complex variations in attenuation, if not accounted for, can severely compromise both the amplitude and phase of the migrated data. This in turn affects the ability to accurately predict reservoir properties. In this paper we propose a new tomographic approach using adaptive centroid frequency shift (CFS) information from surface seismic data to estimate Q.
By picking the events in the migrated section and ray-tracing back to the unmigrated data domain, the centroid frequency of the unmigrated data can be measured for the picked events in the depth migrated CIG gathers. After applying the correction generated on the fly for the given source wavelet, these adaptively corrected CFS will then be back-projected along ray path to reconstruct the attenuation distribution through our tomographic inversion.
A synthetic test and a real data example will be presented to demonstrate how our approach can accurately estimate a Q model and can be included in the Q compensation process to fully account for the frequency dependent attenuation effects observed on seismic data.
A key element of the CFS method is deciding what analytical function should be used to fit the amplitude spectrum of wavelets before and after passing through visco-acoustic media. However, we found the accuracy of Q tomographic inversion to be sensitive to the accuracy of the fitting and that the fixed wavelet fitting function cannot describe the real source wavelet accurately. An adaptive correction is applied to the observed centroid frequency to account for any deviation from the explicit relationship through tabulating the absorption effect for different accumulated dissipation time. These adaptively corrected centroid frequency shifts improve the stability and the accuracy of the inversion.
The propagation of seismic waves through viscoacoustic media is affected by frequency dependent absorption which results in loss of signal strength and bandwidth. Complex variations in attenuation, if not accounted for, can severely compromise both the amplitude and phase of the migrated data. This in turn affects the ability to accurately predict reservoir properties (Best et al., 1994). Thus, there is a need to compensate for the frequency dependent absorption during the processing of the data.
The relation between these two spectra could be expressed as R(f) GH( f) S( f) w here G is assumed to be a frequency independent factor including the effects of geometrical spreading, reflection/transmission coefficients, etc. H(f) describes the attenuation effect, which is formulated as H(f) exp f /(Qv) dl exp f dt (1) ray ray w her e Q is t he q uali ty f ac tor, here we assume Q is frequency independent, v is the seismic wave velocity, and 2014 SEG SEG Denver 2014 Annual Meeting DOI http://dx.doi.org/10.1190/segam2014-0421.1 Page 3726 Robust Q tomographic inversion through adaptive extraction of spectral features * dt is the dissipation time integrating the effects of both velocity and Q along the ray path. At frequency f a and f b, we have R( f a) G exp(f t*) S( f R( f) G exp(f t*) S( f) b a b where R(f a) an d R(f b) ar e the RMS amplitude of the frequency bands whose central frequency are f a and f b, re sp ectively. Which will lead to R( f R ( f a b a b) (2)) S( f a) e xp ((f a fb) t *) (3)) S( f) f or a give n source wavelet, S(f a)/S(f b) is a c on stant value, thus R( f) a S( fa) ln ln ( f b fa) t* a b t * R( fb) (4) S( fb) where a and b are co n st ant values. This shows the accumulated dissipation time is linearly related to the log of the spectrum ratio of two different frequency bands before and post absorption.