Seismic data from the Niger Delta is used to test processing sequences involved in
prestack and poststack amplitude and frequency analysis of marine seismic data. Water
bottom reverberations are found to present a formidable challenge in poststack frequency
and amplitude analysis. However, reflectors with anomalously high amplitudes show low
frequency content both in deconvolved poststack data and in the near offsets of prestack
data with no deconvolution, which agrees with results in the literature. Lack of detailed
knowledge of the lithology prevents investigation of the physical nature of the amplitude
and frequency variations.Massachusetts Institute of Technology. Borehole Acoustics and Logging ConsortiumMassachusetts Institute of Technology. Earth Resources Laboratory. Reservoir Delineation
Consortiu

Burns, Daniel R.

Krasovec, Mary L.

Toksoz, M. Nafi

DSpace@MIT

FREQUENCY DEPENDENCE OF SEISMIC DATAFROM NIGERIA: PRELIMINARY RESULTSMary L. Krasovec, Daniel R. Burns, and M. Nafi ToksozEarth Resources LaboratoryDepartment of Earth, Atmospheric, and Planetary SciencesMassachusetts Institute of TechnologyCambridge, MA 02139ABSTRACTSeismic data from the Niger Delta is used to test processing sequences involved inprestack and poststack amplitude and frequency analysis of marine seismic data. Waterbottom reverberations are found to present a formidable challenge in poststack frequencyand amplitude analysis. However, reflectors with anomalously high amplitudes show lowfrequency content both in deconvolved poststack data and in the near offsets of prestackdata with no deconvolution, which agrees with results in the literature. Lack of detailedknowledge of the lithology prevents investigation of the physical nature of the amplitudeand frequency variations.INTRODUCTIONRecent research suggests the usefulness of frequency content analysis of seismic data.For example, Eastwood et at. (1994) found a correlation between the attenuation ofhigh frequencies and the presence of gas in a shallow bitumen reservoir undergoingsteam injection. Schmitt (1998) found instantaneous frequencies to be 20-30 Hertzlower near well bores during steam injection, coinciding with anomalously high reflectionamplitudes. Radovich and Oliveros (1998) use instantaneous amplitudes and frequenciesto map deep sand channels, finding high amplitudes and low frequencies in the clean,coarse sands. In this case, the low frequency content is attributed to the geometry of thesands. Shen (1998) finds correlation between the presence of fractures and the scatteringof high frequencies and uses frequency variation with offset (FVO) and azimuth to mapfracture set orientations.We note that frequency dependence, like amplitude variation with offset (AVO),can have many different lithological and geometrical causes and is difficult to interpret.12-1Krasovec et al.To date there are relatively few detailed theoretical studies of the rock physics behindfrequency variation. This paper is part of an ongoing project to quantify the causes offrequency variation.SEISMIC DATAOur data is from the Niger Delta off the west coast of Africa. Producing fields in the areaare characterized by marine shales with local sandy and silty beds thought to have beenlaid down as turbidites and continental slope channel fills (Ibie, 1997). The structure ofthe Niger Delta is predominantly characterized by listric faults with associated rolloveranticlines. The facies consist of interbedded high-energy deltaic sandstones, siltstonesand shales, and the region is known to have large reserves of natural gas.A stacked section of our data set (Figure 1) shows some of the features mentionedabove. Since well log data has not been released, this data set is being used only as a testof the processing sequence and frequency calculations. Our knowledge of the regionalgeology does allow a basic interpretation of the section: We see listric normal faultstrending upper left to lower right, and we interpret the shallow bright reflector at CDPs220 through 270 and two-way time 0.6 seconds, to be a gas reservoir. The bright spotat CDP 300 to 350 and two-way time 1.5 seconds could also be a hydrocarbon reservoir.Figure 1 shows four reflectors of interest; the shallowest two, reflectors 1 and 2, passabove and through the shallow bright spot. Reflectors 3 and 4 are deeper horizonsthat appear to terminate at the fault. Reflector 3 shows an increase in amplitude nearthe fault, suggesting an accumulation of hydrocarbons sealed by the fault. We willconcentrate on these reflectors in our analysis, with reflectors 1 and 4 assumed to bebackground, and the brighter parts of reflectors 2 and 3 being anomalies.Our processing sequence attempts to preserve the amplitude and spectrum of thedata as much as possible. We use spheri~al divergence amplitude corrections and applyan FK filter to minimize the water bottom reverberations. Figure 2a shows the shotgather with only gain corrections and a band pass filter to remove low frequency noise,Figure 2b shows the same shot gather after FK filtering. To pick the horizons of interest,we apply deconvolution and do a velocity analysis, then stack the data as shown inFigure 1. From the stack we choose the zero offset times and stacking velocities ofthe events of interest. We use these to define a moveout curve in the prestack domain(with no deconvolution), such as the solid line shown for synthetic data in Figure 3. Awindow of constant width is taken at each offset, shown as dashed lines. The traces ineach window are then analyzed for amplitude and frequency content, shown in Figure 4.We use two methods of frequency analysis: Instantaneous properties derived fromcomplex trace analysis (Taner et ai., 1979) and the multiple signal classification (MU-SIC) method (Schmidt, 1986), which is useful for power spectrum estimation of shorttraces (Shen, 1998).Following the method of Shen (1998) we describe the frequency dependence of thepoststack data by doing a linear least square fit of peak frequency versus offset, re-12-2Frequency Dependence of Seismic Data From NigeriasuIting in values for FVO slope and FVO intercept at each point along the poststackreflector. Similarly, for the amplitude variation, we estimate the incidence angle e foreach poststack trace and find AVO slope and AVO intercept from a plot of amplitudeversus sin2 e.RESULTSFigures 5 and 6 are the frequency and amplitude analysis results for two CMP locationsalong horizon 3, at about 1,550 ms. Figure 5 is taken at CMP 315, where the stackshows a bright spot. Figure 6 is at CMP 425 further along the horizon, where thereflection is not so bright.We note that the plot of frequency versus offset has a great deal of scatter. In fact,no clear correlation between peak frequency and offset is found conclusively. This isobvious from the lack of coherent peaks in the traces, shown in the top subplot.The amplitude versus angle plot shows similar problems. We note the suddenchanges in amplitude at middle offsets, part of which we attribute to an artifact ofthe FK filtering of the linear arrivals. Figures 2a and 2b show the unevenness of reflec-tors amplitudes in shot gathers, with and without FK filtering.Figure 7 shows the FVO slope for the four horizons. We see that the values areall extremely small and show no correlation with the bright amplitude regions. On theother hand, the FVO intercept shown in Figure 8 shows low frequencies in the regionswith bright reflections.Figure 9 shows the instantaneous frequency for the four horizons of interest in thedeconvolved poststack data. The bright reflectors show low frequencies in agreementwith the poststack FVO intercepts shown in Figure 8.CONCLUSIONSPreliminary results show, both in the poststack domain and at near offsets, a correla-tion between low frequency content and large amplitude reflections in areas thought tocontain hydrocarbon reservoirs. However, linear arrivals in the raw data due to directwaves and water bottom reverberations severely limit our ability to analyze the data inthe prestack domain. Future processing schemes need to address this issue.ACKNOWLEDGMENTSThis work was supported by the Borehole Acoustics and Logging/Reservoir DelineationConsortia at the Massachusetts Institute of Technology.12-3Krasovec et al.REFERENCESEastwood, J., Lebel, P., Dilay, A., and Blakeslee, S., 1994, Seismic monitoring of steam-based recovery of bitumen, The Leading Edge, 13, 242-25l.Ibie, E., 1997, Seismic stratigraphic analysis in the Niger Delta: A case study of theBenin River 3-D seismic cube, M.S. thesis, Massachusetts Institute of Technology.Radovich, B.J., and RB. Oliveros, 1998, 3-D sequence interpretation of seismic instan-taneous attributes from the Gorgan field, The Leading Edge, 11, 1286-1293.Schmidt, R, 1986, Multiple emitter location and signal parameter estimation, IEEETransaction on Antennas and Propagation, AP-34, 276-280.Schmitt, D.R., 1998, Seismic Attributes for monitoring of a shallow heated heavy oilreservoir: A case study, Geophysics, 63, 368-377.Shen, F., 1998, Seismic characterization of fractured reservoirs (Part I); Crustal defor-mation in the Tibetan plateau (Part II), Ph.D. thesis, Massachusetts Institute ofTechnology.Taner, M.T., Koehler, F., and Sheriff, RE., 1979, Complex seismic trace analysis, Geo-physics, 44, 1041-1063.12-4Frequency Dependence of Seismic Data From NigeriaFigure 1: The stacked section with a possible fault location and horizons of interestmarked. Horizons 1 and 2 pass above and through the shallow bright spot. Reflec-tors 3 and 4 are deeper horizons that appear to terminate near the fault.12-5Krasovec et al.Relative Offset (ft)1000 2000 3000 40Figure 2a: A shot gather with spherical divergence amplitude correction and bandpassfor low frequency noise.12-6Frequency Dependence of Seismic Data From NigeriaRelative Offset (ft)1000 2000 3000 40Figure 2b: The same shot gather as in Figure 2a with FK filtering applied.12-7Krasovec et al.two way timeo...... r_---------------.-/'0> t--------------..........~r_--------------~......0>.....(1)'0(1).:c::.I\)(1)...........~t-----------~-- .....~t_-------------!--~ t_-------------"Figure 3: Synthetic data to illustrate the windowing process. See text for detaileddescription.12-83000Frequency Dependence of Seismic Data From Nigeria1.62O~-----~~.L-.L--L---=-=~ "-__~~ll....-.llL-L"""LLLLLL ---.l1500 2000 2500offset (m)Q)E 1.56;j1ii~ 1.58oo~ 1.63000250020001500offset (m)•• •• • • •• • ••• •• •• • • •• ••500 1000 1500 2000 2500 3000offset (m)•••• •• • • •••2 4 6 8 10 12 14roo 60NE.;>.g 40Q)::l0"~- 20040N!-35>.u•~ 30::J~25-"i 20Q)Q.150x 10510Gl'tl 8 •:l~Q.E 6tllc:tllGl 4E20angleFigure 4: Offset dependent frequency and amplitude calculation for synthetic datashown in Figure 3. The top plot shows the traces chosen by the windowing. Thesecond plot is the power spectrum where lighter means more power. The third plotshows the peak frequency, and the bottom plot shows the amplitude versus incidenceangle.12-9Krasovec et al.0.55Q):§ 0.6Q)en15 0.65eQ)NO.7o 200 400 600 800 1000 1200offset (m)1400 1600 1800 20002000180016001400800600400200Ol-__-L L-__-L.__----I -L.__----l ...l-__-.J. ..l.-__-Jo 1000 1200offset (m)30,-------rT----r-I----r'----,---I-..... -'I----,---..,-----,-------.------,30---• •N~25>.g 20Q):JI15.::s:. •• • ••~ 10 ~.;e.~.~.~.•~~.,..~.;t.r~.;-1r.....--..rt.r---.~=-~~ -=-:-::-:::- j-- I • • •• • ••••••5L-__..l...- --L.__-L~_ __l...__--I.__---l ~~~~~~o 200 400 600 800 1000 1200 1400 1600 1800 2000x 10-5 offset (m)1.3 r-----r------.----,-------,r-------r---,-----r-------.----,~ 1.25.3'5. 1.2Ettlc 1.15ttlQ)E 1.15 10 15 20 25 30 35 40 45angleFigure 5: Frequency and amplitude analysis results for horizon 3 at CDP 315. SeeFigure 4 caption for subplot description.12-10Frequency Dependence of Seismic Data From Nigeria~ 1.64Q)l/l 1.6615:~ 1.68N1500offset (m)2000 2500 3000~60N6>-g 40Q):lc:r~- 200 500 1000 1500 2000 ·2500 3000offset (m)70N • •660>- •() •~ 50 • • •:J~ 40 • • • • • •• •- • •~ 30 • •Q)• •Q.• •200 500 1000 1500 2000 2500 3000x 105offset (m)8Ql • •"06 •.~ •a. •E4 • • •III • •c: • •til• • • • • • • • • •~2 • •• •00 2 4 6 8 10 12 14angleFigure 6: Frequency and amplitude analysis results for horizon 3 at CDP 425. SeeFigure 4 caption for subplot description.12-11c.«_«-.'0.60.8j1rCll[_~c_,,«._c._««,c_c« (__"--.«i«e:_ ..'·"l. (C-t'C_C:_~_c-... ....__c....-.c._.._ ...1.2~(j)'"in.PlO(llUiOo~[rC"l(l)&Pl..--0.60··C:__·~IaJ"'_(CC._l~-..._u -...__15021.82.22.4~I I I I I I200 250 300 350 400 450 500COP1.4(j)E:;::>.ro~ ~ 1.6r-' 3:l'V _Figure 7: The FVa slope for all four horizons.I .60.00.06 . .«C4["-:.«......_. , «Ul«C_«."CCC~,---_.~._-c..-.....-_• • '.C:.". ___.._. ccccc.._-~_u__ _._, ,_.~««-c..c.(1)~ •.•C••C4[(<C~,.0.::0.8(1)I I i:J...jC"l'<tj(1)'i;j0.(1)OJ i:J~ p...1.2 f-OJ (1)C i:J37.50 0 g> 0IJ...H,1.4rn(C__...-'"''''''~-'''- .r".._r......"..._,.• ,.......(1)OJ......E(fJ+::S>-......CllC"l~ 1.6tj0~-l-Plc+>-'Pltv~I1.8>-'w1,5000,..,---J s2:2f-............<- .-._~-_ ..._~()q(1)'1......Pl2.2f--!500I4504002.4 f-350I300250COP200150Figure 8: The FVO intercept for all four horizons.-----------Cl:;(<<c..-c. l{«<_ _O.6r--!-.- c.. n. .,a._c. (0.81.2«c< «<f: _.'«ITIII .60>-'l--:JI>-'"""Q)1.4E:;::;>-CI:l~ 1.6o~-+-'1.822.22.4150 200 250 300CDP350---.-. ............ <-.. ......~-400:"450-"__e.~ __J500~.,~30 ~("lCliC"t-Pl......oFigure 9: The instantaneous frequency for all four horizons, calculated from the decon-volved poststack data.

Frequency Dependence Of Seismic Data From Nigeria: Preliminary Results

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Frequency Dependence Of Seismic Data From Nigeria: Preliminary Results

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