Magnetic anomaly interpretation for a 2D fault-like geologic structures utilizing the global particle swarm method

doi:10.21203/rs.3.rs-785255/v1

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Magnetic anomaly interpretation for a 2D fault-like geologic structures utilizing the global particle swarm method

https://doi.org/10.21203/rs.3.rs-785255/v1

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We establish a method to elucidate the magnetic anomaly due to 2D fault structures, with an evaluation of first moving average residual anomalies utilizing filters of increasing window lengths. After that, the buried fault parameters are estimated using the global particle swarm method. The goodness of fit among the observed and the calculated models is expressed as the root mean squared (RMS) error. The importance of studying and delineating the fault parameters, which include the amplitude factor, the depth to the upper edge, the depth to the lower edge, the fault dip angle, and the position of the origin of the fault, is: (i) solving many problem-related engineering and environmental applications, (ii) describing the accompanying mineralized zones with faults, (iii) describing geological deformation events, (iv) monitoring the subsurface shear zones, (v) defining the environmental effects of the faults before organizing any investments, and (vi) imaging subsurface faults for different scientific studies.

Finally, we show the method applied to two theoretical models including the influence of the regional background and the multi-fault effect and to real field examples from Australia and Turkey. Available geologic and geophysical information corroborates our interpretations.

Environmental Engineering

Geology

Global particle swarm

moving average

fault

depth

Table 1. Numerical results due to the application of the global particle swarm method for the first moving average residual magnetic anomalies using several s-values for a 2D fault with K= 400 nT, K, z₁ = 4 km, z₂ = 7 km, θ = 35^o, β = 30^o, c = 50 km, and profile length = 100 km and a first-order impeded regional field anomaly without, with a 10% noise level.

Parameters	Used ranges	Applying the particle swarm method for the first moving average magnetic data
		with a 0% noise level
		s = 3 km	s = 5 km	s = 7 km	s = 9 km	s = 11 km	μ	δ (%)	λ (nT)
K (nT)	100-1000	398.23	398.67	399.14	399.50	399.86	399.08±0.65	0.23	0.22
z₁ (km)	1-20	3.99	3.99	4.00	3.99	4.00	3.99±0.01	0.15
z₂ (km)	1-20	6.98	6.98	7.00	7.01	6.99	6.99±0.01	0.11
θ (^o)	10-80	34.96	34.99	34.99	34.99	35.00	34.99±0.02	0.04
β (^o)	10-80	29.97	29.99	30.01	30.00	30.00	29.99±0.02	0.02
c (km)	10-100	49.98	49.98	49.98	50.01	50.01	49.99±0.02	0.02
with a 10% noise level
K (nT)	100-1000	382.95	383.13	387.47	389.69	390.24	386.70±3.50	3.33	22.01
z₁ (km)	1-20	3.74	3.80	3.84	3.87	3.92	3.83±0.07	4.15
z₂ (km)	1-20	6.71	6.75	6.77	6.81	6.85	6.78±0.05	3.17
θ (^o)	10-80	32.98	33.36	33.61	34.12	34.38	33.69±0.57	3.74
β (^o)	10-80	27.63	28.02	28.14	28.56	29.06	28.28±0.55	5.73
c (km)	10-100	47.56	47.88	49.15	49.30	49.67	48.71±0.93	2.58

Table 2. Numerical results due to the application of the global particle swarm method for the first moving average residual magnetic anomalies using several s-values for the multi-2D faults without and with a 10% noise level.

Model	Parameters	Used ranges	Applying the particle swarm method for the first moving average magnetic data
			with a 0% noise level
			s = 3 km	s = 5 km	s = 7 km	s = 9 km	s = 11 km	μ	δ (%)	λ (nT)
Body1	K (nT)	100-500	285.13	288.10	291.32	293.27	294.96	290.56±3.96	3.15	12.81
	z₁ (km)	1-20	2.91	2.91	2.95	2.93	2.95	2.93±0.02	2.33
	z₂ (km)	1-20	9.84	9.87	9.92	9.93	9.96	10.00±0.05	0
	θ (^o)	10-170	117.11	117.64	118.14	119.02	119.00	118.18±0.84	1.52
	β (^o)	10-80	18.81	19.19	19.50	19.85	19.93	19.46±0.47	2.72
	c (km)	10-100	52.05	52.48	52.66	52.84	52.94	52.59±0.35	0.77
Body2	K (nT)	100-500	192.09	194.26	195.72	196.90	196.88	195.17±2.03	2.41
	z₁ (km)	1-20	4.58	4.70	4.76	4.92	4.92	4.78±0.15	4.48
	z₂ (km)	1-20	8.23	8.68	8.94	9.23	9.54	8.92±0.50	10.76
	θ (^o)	10-170	129.44	132.31	136.00	136.05	136.38	134.04±3.06	0.71
	β (^o)	10-80	18.06	18.42	19.02	19.54	19.80	18.97±0.73	5.16
	c (km)	10-100	45.33	45.94	46.28	46.61	46.94	46.22±0.62	1.66
with a 10% noise level
Body1	K (nT)	100-500	271.24	276.76	283.81	285.25	293.59	282.13±8.53	5.96	26.07
	z₁ (km)	1-20	2.82	2.86	2.90	3.01	2.97	2.91±0.08	2.93
	z₂ (km)	1-20	8.75	9.10	10.12	9.91	9.93	9.56±0.60	4.38
	θ (^o)	10-170	114.36	116.71	118.25	121.48	123.81	118.92±3.76	0.90
	β (^o)	10-80	18.19	20.03	19.86	20.57	21.14	19.96±1.11	0.21
	c (km)	10-100	50.48	51.05	51.74	52.60	53.25	51.82±1.12	2.22
Body2	K (nT)	100-500	185.03	188.17	193.44	199.00	204.13	193.95±7.78	3.02
	z₁ (km)	1-20	4.41	4.74	4.92	5.13	5.20	4.88±0.32	2.40
	z₂ (km)	1-20	8.15	8.49	9.26	9.74	10.04	9.14±0.80	8.64
	θ (^o)	10-170	130.36	132.06	133.57	134.61	134.85	133.09±1.88	1.41
	β (^o)	10-80	17.47	18.11	18.85	18.92	19.53	18.58±0.80	7.12
	c (km)	10-100	46.22	47.23	47.62	47.85	47.85	47.35±0.68	0.75

Table 3. Numerical results due to the application of the global particle swarm method for the first moving average residual magnetic anomalies using several s-values for the Perth Basin field example, Australia.

Parameters	Used ranges	Applying the particle swarm method for the first moving average magnetic data
Parameters	Used ranges	s = 3 km	s = 5 km	s = 7 km	s = 9 km	s = 11 km	μ	λ (nT)
K (nT)	50-500	145.19	146.03	146.72	147.34	147.80	146.62±1.04	7.18
z₁ (km)	1-20	5.65	5.87	5.93	6.12	6.34	5.98±0.26
z₂ (km)	1-20	14.58	14.76	14.98	15.17	15.48	14.99±0.35
θ (^o)	10-170	95.27	95.68	95.42	95.91	95.91	95.64±0.29
β (^o)	-80-+80	-18.84	-19.59	-21.35	-22.48	-23.43	-21.14±1.92
c (km)	5-40	17.41	17.90	18.24	18.53	18.17	18.05±0.42

Table 4. A comparative study of the results obtained for the Perth Basin Field example, Australia.

Methods	K	z₁ (km)	z₂ (km)	θ (^o)	β (^o)	c (km)
Qureshi and Nalaye (1978)	-----	5.80 to 6.85	15.55 to 17.00	30	-----	-----
Rao and Babu (1983)	-----	6.26	15.45	40
Asfahani and Tlas (2007)	200.30±28.30	7.5±1.00	14±1.60	39.80±1.30	-----	-----
Tlas and Asfahani (2011)	200.56	7.22	13.72	35.56	-----	0.88
Di Maio et al. (2020)	169.40±4.00	8.50±0.20	12.00±0.02	35.86±0.01	-----	0.80±0.01
This study	146.62±1.04	5.98±0.26	14.99±0.35	95.64±0.29	-21.14±1.92	18.05±0.42

Table 5. Numerical results due to the application of the global particle swarm method for the first moving average residual magnetic anomalies using several s-values for the Aksaray fault field example, Turkey.

Parameters	Used ranges	Applying the particle swarm method for the first moving average magnetic data
Parameters	Used ranges	s = 1.875 km	s = 3.125 km	s = 4.375 km	s = 5.625 km	s = 6.875 km	μ	λ (nT)
K (nT)	50-500	144.14	145.35	147.72	146.28	146.84	146.07±1.38	25.93
z₁ (km)	1-20	1.86	1.91	1.95	2.04	1.98	1.95±0.07
z₂ (km)	1-20	4.53	4.46	4.51	4.67	4.83	4.60±0.15
θ (^o)	10-170	162.09	162.67	163.10	164.15	164.42	163.29±0.98
β (^o)	5-80	32.96	33.08	33.42	33.83	34.11	33.48±0.49
c (km)	525-550	536.18	539.21	541.83	542.34	543.08	540.53±2.83

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Magnetic anomaly interpretation for a 2D fault-like geologic structures utilizing the global particle swarm method

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