In recent years, the controlled-sources electromagnetic method has been widely applied for oil and metallic ore exploration. It is necessary to study the effects of the constituents and microstructure in pyrite-bearing hydrocarbon-bearing reservoir sandstones on 3D marine controlled source electromagnetic sounding, so as to improve the accuracy of the marine controlled sources electromagnetic (MCSEM) Method. In this paper, we present a new finite element algorithm for 3D MCSEM modeling, which is based on unstructured grids. In the modeling, we adopted the secondary formulation for the quasi-static variant of Maxwell’s equation, so that the source singularity could be avoided effectively. We first applied the four-phase incremental model to calculate the conductivity of the pyrite-bearing hydrocarbon. This is of use in studying the electrical conductivity of pyrite-bearing sandstones. The finite element equations were solved by means of the preconditioned IDR(s) method. We applied our algorithm to calculate the response of various key parameters of MCSEM (i.e. pyrite content, porosity, pyrite conductivity, grain aspect ratio and water saturation). The results of the modeling show the performance of the algorithm, and are expected to assist in future CSEM data interpretation when a pyrite-bearing sandstone reservoir is encountered.
ConstableS. and SrnkaL.J., An introduction to marine controlled-source electromagnetic methods for hydrocarbon exploration, Geophysics72 (2007), WA3–WA12.
2.
LiuC.S.EverettM.E.LinJ. et al., Modeling of seafloor exploration using electric-source frequency-domain CSEM and the analysis of water depth effect, Chinese J. Geophys. (in Chinese)53(8) (2011), 1940–1952.
3.
LiuY. and LiY.G., Marine electromagnetic response of arbitrarily oriented electric dipole in layered anisotropic media, Oil Geophysical Prospecting (04) (2015), 755–765.
4.
HussainN.KarsitiM.N.JeotiV. and YahyaN., Use of wavelets in marine controlled source electromagnetic method for geophysical modeling, International Journal of Applied Electromagnetics and Mechanics (2016), 431–443, doi: 10.3233/JAE-160002.
5.
AngiulliG.CacciolaM.CalcagnoS.De CarloD.MorabitoC.F.SgróA. and VersaciM., A numerical study on the performances of the flexible BiCGStab to solve the discretized E-field integral equation, International Journal of Applied Electromagnetics and Mechanics46(3) (2014), 547–553, doi: 10.3233/JAE-141939.
6.
UnsworthM.TravisB. and ChaveA., Electromagnetic induction by a finite electric dipole source over a 2D earth, Geophysics58(2) (1993), 198–214.
7.
SongX.JiangL.Y.MihaiR. and SykulskiJ.K., Considerations of uncertainty in robust optimisation of electromagnetic devices, International Journal of Applied Electromagnetics and Mechanics46(2) (2014), 427–436.
8.
HussainN.KarsitiM.N.YahyaN.JeotiV. and YahyaN., 2D wavelets Galerkin method for the computation of EM field on seafloor excited by a point source, International Journal of Applied Electromagnetics and Mechanics53 (2017), 631–644, doi: 10.3233/JAE-160028.
9.
LiY. and KeyK., 2D marine controlled-source electromagnetic modeling: Part 1 – An adaptive finite-element algorithm, Geophysics72(2) (2007), WA51–WA62.
10.
ShenJ.S. and SunW.B., Numerical simulation of ocean electromagnetic response of controlled source in two dimensional seabed, Geophysical Prospecting for Petroleum48(2) (2009), 188–194.
11.
KerryK. and JeffreyO., A parallel goal-oriented adaptive finite element method for 2.5-D electromagnetic modelling, Geophys. J. Int.186 (2011), 137–154.
12.
LiuY., A paralleled adaptive finite element method for 2-D marine controlled-source electromagnetic forward modeling, The 10 China International Geo-Electromagnetic Workshop, 2011.
13.
ChenG.B.WangH.N.YaoJ.J. and HanZ.Y., Numerical simulation of three dimensional integral equation method for electromagnetic response of ocean controlled source in anisotropic seabed, ACTA PHYSICA SINICA (06) (2009), 3848–3857.
14.
TangJ.T.RenZ.Y. and HuaX.R., Theoretical analysis of geo-electromagnetic modeling on Coulomb gauged potentials by adaptive finite element method, Chinese J. Geophys. (in Chinese)50(5) (2007), 1584–1594.
15.
SchwarzbachC.BörnerR.U. and SpitzerK., Three-dimensional adaptive higher order finite element simulation for geo-electromagnetics-a marine CSEM example, Geophys. J. Int.187 (2011), 63–74, doi: 10.1111/j.1365-246X.2011.05127.x.
16.
YangB.XuY.X. and HeZ.X., 3D frequency-domain modeling of marine controlled source electromagnetic responses with topography using finite volume method, Chinese J. Geophys. (in Chinese)55(4) (2012), 1390–1399.
17.
PuzyrevV.KoldanJ.PuenteJ. and HouzeauxG., A parallel finite-element method for three-dimensional controlled-source electromagnetic forward modelling, Geophys. J. Int.193 (2013), 678–693, doi: 10.1093/gii/ggt027.
18.
YangJ.LiuY. and WuX.P., 3D simulation of marine CSEM using vector finite element method on unstructured grids, Chieses J. Geophys. (in Chinese)58(8) (2015), 2827–2838.
19.
YinC.C.BenF. and LiuY.H., MCSEM 3D modeling for arbitrarily anisotropic media, Chinese J. Geophys. (in Chinese)57(12) (2014), 4110–4122.
20.
CaiH.Z.XiongB. and ZhdanovM., Three-dimensional marine controlled-source electromagnetic modeling in anisotropic medium using finite element method, Chinese J. Geophys. (in Chinese)58(8) (2015), 2839–2850.
21.
JahandariH. and FarquharsonC.G., Finite-volume modelling of geophysical electromagnetic data on unstructured grids using potentials, Geophys. J. Int.202 (2015), 1859–1876.
22.
ConstableS., Ten years of marine CSEM for hydrocarbon exploration, Geophysics75 (2010), A67–A81.
23.
ManningM.J. and AthavaleK.A., Dielectric properties of pyrite samples at 1100 Mhz, Geophysics51 (1986), 172–182.
24.
SternbergB., A review of some experience with the induced-polarization/resistivity method for hydrocarbon surveys: Successes and limitations, Geophysics56(10) (1991), 1522–1532.
25.
UlrichC. and SlaterL., Induced polarization measurements on unsaturated, unconsolidated sands, Geophysics69(3) (2004), 762–771.
26.
HeZ.X. and WangX.B., Abnormal patterns of oil and gas reservoirs and electromagnetic method for hydrocarbon detection, Oil Geophysical Prospecting42(1) (2007), 102–106.
27.
VeekenPP.LegeydP. and DavidenkoY., Benefits of the induced polarization geoelectric method to hydrocarbon exploration, Geophysics74(2) (2009), B47–B59.
28.
ClennellM.B.JoshM.EstebanL.HillD.WoodsC.McMullanB.DellePianeC.SchmidS. and VerrallM., The influence of pyrite on rock electric properties: a case study from NWAustralian gas reservoirs, in: 51st SPWLA Annual Logging Symposium, Paper UUU, 2010.
29.
GuoN.N.ChangY.J. and JiaH.T., Influences of induced polarization on marine controlled-source electromagnetic survey, in: The 10th China International Geo-Electromagnetic Workshop, 2011, pp. 392–395.
30.
ArchieG.E., The electrical resistivity log as an aid in determining some reservoir characteristics, Trans, Am. Inst. Min. Metall. Eng.146 (1942), 54–62.
31.
BruggemanD.A.G., Berechnung verschiedener physikalischer konstanten von heterogenen Substantzen, Ann. Phys24 (1935), 636–664.
32.
HanaiT., Theory of the dielectric dispersion due to the interfacial polarization and its application to emulsions, Kolloid Zeitschrift171 (1960a), 23–31.
33.
AsamiK., Characterization of heterogeneous systems by dielectric spectroscopy, Prog. Polym. Sci.27 (2002), 1617–1659.
34.
HanT.ClennellM.B.JoshM. and PervukhinaM., Determination of effective grain geometry for electrical modeling of sedimentary rocks, Geophysics80 (2015), D319–D327.
35.
ZhdanovM.S., Geophysical electromagnetic theory and methods, Elsevier, 2009, 235–276, doi: 10.1029/2001RS002513.
36.
JinJ., Finite Element Method in Electromagnetic, Wiley-IEEE Press, 2002 New York.
37.
SonneveldP. and van GijzenM.B., IDR(s): a family of simple and fast algorithms for solving large nonsymmetric systems of linear equations, SIAM J. Sci. Comput31(2) (2008/09), 1035–1062, doi: 10.1137/070685804.
