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<![CDATA[Multi-dimensional Inversion Modeling of Surface Nuclear Magnetic Resonance (SNMR) Data for Groundwater Exploration ]]>
<![CDATA[Warsa, W.]]>;
<![CDATA[Grandis, Hendra]]>;
<![CDATA[Parnadi, Wahyudi W.]]>;
<![CDATA[Santoso, Djoko]]>
<![CDATA[ Journal of Engineering and Technological Sciences Vol 46, No 2 (2014) ]]>
Publisher : <![CDATA[ITB Journal Publisher, LPPM ITB ]]>
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DOI: 10.5614/j.eng.technol.sci.2014.46.2.1
<![CDATA[Groundwater is an important economic source of water supply for drinking water and irrigation water for agriculture. Surface nuclear magnetic resonance (SNMR) sounding is a relatively new geophysical method that can be used to determine the presence of culturally and economically important substances, such as subsurface water or hydrocarbon distribution. SNMR sounding allows the determination of water content and pore size distribution directly from the surface. The SNMR method is performed by stimulating an alternating current pulse through an antenna at the surface in order to confirm the existence of water in the subsurface. This paper reports the development of a 3-D forward modeling code for SNMR amplitudes and decay times, after which an improved 2-D and 3-D inversion algorithm is investigated, consisting of schemes for regularizing model parameterization. After briefly reviewing inversion schemes generally used in geophysics, the special properties of SNMR or magnetic resonance sounding (MRS) inversion are evaluated. We present an extension of MRS to magnetic resonance tomography (MRT), i.e. an extension for 2-D and 3-D investigation, and the appropriate inversions.]]>
<![CDATA[LAYER STRIPPING IN MAGNETOTELLURICS (MT) FOR ENHANCEMENT OF RESISTIVITY CHANGE EFFECT IN RESERVOIR: EQUIVALENCE ANALYSIS ]]>
<![CDATA[Grandis, Hendra]]>;
<![CDATA[Warsa, W]]>;
<![CDATA[Sumintadireja, Prihadi]]>
<![CDATA[ Journal of Engineering and Technological Sciences Vol 52, No 2 (2020) ]]>
Publisher : <![CDATA[Institute for Research and Community Services, Institut Teknologi Bandung ]]>
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DOI: 10.5614/j.eng.technol.sci.2020.52.2.9
<![CDATA[Magnetotellurics (MT) can be applied to monitor resistivity change at depth that is for example due to fluid injection in enhanced oil recovery or CO2 storage. The observed MT data changes at the surface may be insignificant, but the effect can be enhanced using the layer stripping method, i.e. calculating MT data changes that would be observed at depth based on data from the surface. Two well-known formulas for MT 1D forward modeling were reformulated to allow for calculation of the impedance at depth based on the impedance at the surface. We applied the layer stripping technique to synthetic data associated with models that were representative of a likely CO2 storage site. We also used an equivalent model and the Monte Carlo approach to estimate the sensitivity of the method to cope with the uncertainty of the host model and the input data. The layer stripping calculation has the greatest uncertainty at short periods, where the real and imaginary parts of the complex impedance tend to be equal, i.e. an homogeneous medium response. The layer stripping technique should be used with great caution based on a relatively precise 1D host model.]]>
<![CDATA[Multi-dimensional Inversion Modeling of Surface Nuclear Magnetic Resonance (SNMR) Data for Groundwater Exploration ]]>
<![CDATA[W. Warsa]]>;
<![CDATA[Hendra Grandis]]>;
<![CDATA[Wahyudi W. Parnadi]]>;
<![CDATA[Djoko Santoso]]>
<![CDATA[ Journal of Engineering and Technological Sciences Vol. 46 No. 2 (2014) ]]>
Publisher : <![CDATA[Institute for Research and Community Services, Institut Teknologi Bandung ]]>
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DOI: 10.5614/j.eng.technol.sci.2014.46.2.1
<![CDATA[Groundwater is an important economic source of water supply for drinking water and irrigation water for agriculture. Surface nuclear magnetic resonance (SNMR) sounding is a relatively new geophysical method that can be used to determine the presence of culturally and economically important substances, such as subsurface water or hydrocarbon distribution. SNMR sounding allows the determination of water content and pore size distribution directly from the surface. The SNMR method is performed by stimulating an alternating current pulse through an antenna at the surface in order to confirm the existence of water in the subsurface. This paper reports the development of a 3-D forward modeling code for SNMR amplitudes and decay times, after which an improved 2-D and 3-D inversion algorithm is investigated, consisting of schemes for regularizing model parameterization. After briefly reviewing inversion schemes generally used in geophysics, the special properties of SNMR or magnetic resonance sounding (MRS) inversion are evaluated. We present an extension of MRS to magnetic resonance tomography (MRT), i.e. an extension for 2-D and 3-D investigation, and the appropriate inversions.]]>
<![CDATA[Layer Stripping in Magnetotellurics (MT) for Enhancement of Resistivity Change Effect in Reservoir: Equivalence Analysis ]]>
<![CDATA[Hendra Grandis]]>;
<![CDATA[W Warsa]]>;
<![CDATA[Prihadi Sumintadireja]]>
<![CDATA[ Journal of Engineering and Technological Sciences Vol. 52 No. 2 (2020) ]]>
Publisher : <![CDATA[Institute for Research and Community Services, Institut Teknologi Bandung ]]>
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DOI: 10.5614/j.eng.technol.sci.2020.52.2.9
<![CDATA[Magnetotellurics (MT) can be applied to monitor resistivity change at depth that is for example due to fluid injection in enhanced oil recovery or CO2 storage. The observed MT data changes at the surface may be insignificant, but the effect can be enhanced using the layer stripping method, i.e. calculating MT data changes that would be observed at depth based on data from the surface. Two well-known formulas for MT 1D forward modeling were reformulated to allow for calculation of the impedance at depth based on the impedance at the surface. We applied the layer stripping technique to synthetic data associated with models that were representative of a likely CO2 storage site. We also used an equivalent model and the Monte Carlo approach to estimate the sensitivity of the method to cope with the uncertainty of the host model and the input data. The layer stripping calculation has the greatest uncertainty at short periods, where the real and imaginary parts of the complex impedance tend to be equal, i.e. an homogeneous medium response. The layer stripping technique should be used with great caution based on a relatively precise 1D host model.]]>
<![CDATA[Global Inversion of Grounded Electric Source Time-domain Electromagnetic Data Using Particle Swarm Optimization ]]>
<![CDATA[Cahyo Aji Hapsoro]]>;
<![CDATA[Wahyu Srigutomo]]>;
<![CDATA[Acep Purqon]]>;
<![CDATA[Warsa warsa]]>;
<![CDATA[Doddy Sutarno]]>;
<![CDATA[Tsuneomi Kagiyama]]>
<![CDATA[ Journal of Engineering and Technological Sciences Vol. 53 No. 1 (2021) ]]>
Publisher : <![CDATA[Institute for Research and Community Services, Institut Teknologi Bandung ]]>
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DOI: 10.5614/j.eng.technol.sci.2021.53.1.1
<![CDATA[Global optimization inversion of grounded wire time-domain electromagnetic (TDEM) data was implemented through application of the particle swarm optimization (PSO) algorithm. This probabilistic approach is an alternative to the widely used deterministic local-optimization approach. In the PSO algorithm, each particle that constitutes the swarm epitomizes a probable geophysical model comprised by subsurface resistivity values at several layers and layer thicknesses. The forward formulation of the TDEM problem for calculating the vertical component of the induced magnetic field is first expressed in the Laplace domain. Transformation of the magnetic field from the Laplace domain into the time domain is performed by applying the Gaver-Stehfest numerical method. The implementation of PSO inversion to the TDEM problem is straightforward. It only requires adjustment of a few inversion parameters such as inertia, acceleration coefficients and numbers of iteration and particles. The PSO inversion scheme was tested on synthetic noise-free data and noisy synthetic data as well as to field data recorded in a volcanic-geothermal area. The results suggest that the PSO inversion scheme can effectively solve the TDEM 1D stratified earth problem. ]]>
<![CDATA[PEMODELAN METODE DEEP SOUNDING TEM UNTUK MONITORING INJEKSI KARBON DIOKSIDA (CO2) PADA RESERVOIR ]]>
<![CDATA[Gatot Nugroho]]>;
<![CDATA[Warsa Warsa]]>
<![CDATA[ Jurnal Geofisika Vol 15 No 2 (2017): Jurnal Geofisika ]]>
Publisher : <![CDATA[Himpunan Ahli Geofisika Indonesia (HAGI) ]]>
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DOI: 10.36435/jgf.v15i2.406
<![CDATA[Pemantauan distribusi CO2 merupakan salah satu hal yang sangat penting dalam keberlanjutan CCS. Sampai saat ini pemantauan geofisika yang sering digunakan adalah metode seismik. Penelitian ini dimaksudkan untuk mengetahui kemampuan metode deep TEM untuk melakukan pemantauan pada CCSmelalui pemodelan metode deep TEM untuk simulasi pemantauan injeksi CO2. Data TEM sebelum dan sesudah dilakukan injeksi CO2 dibandingkan untuk mengetahui pengaruh keberadaan CO2. Data TEM sebelum injeksi diperoleh dari pengukuran di lapangan pada tahun 2013. Data TEM setelah injeksi diperoleh dari hasil pemodelan ke depan dengan parameter model yang diperoleh dari hasil inversi data TEM lapangan. Pemodelan inversi dilakukan dengan menggunakan metode inversi SVD damped least square. Proses inversi SVD digunakan untuk mengidentifikasi reservoir dan memetakan distribusi CO2pada reservoir. Hasil pemodelan inversi satu dimensi diolah menjadi model dua dimensi dengan menggunakan perangkat lunak Rockworks16. Hasil pemodelan inversi data TEM lapangan menunjukkan bahwa reservoir mempunyai resistivitas rendah yaitu 2 Ωm sampai 4 Ωm. Reservoir ini berada pada kedalaman 900 m sampai 1200 m di bawah permukaan. Perbandingan data TEM sebelum injeksi CO2 dan setelah injeksi CO2 menunjukkan adanya pengaruh CO2 terhadap kurva data TEM sebelum dan setelah injeksi CO2 secara jelas. Pola kurva data TEM setelah injeksi menenjadi lebih curam pada bagian tengah dari pada kondisi sebelum ada injeksi CO2. Perubahan kurva TEM yang menjadi lebih curam tersebut disebabkan oleh keberadaan CO2 pada reservoir meningkatkan resistivitas reservoir. Lapisan reservoir setelah injeksi mempunyai resistivitas yang lebih tinggi membuat waktu peluruhan medan elektromagnetik pada lapisan tersebut menjadi lebih cepat, sehingga kurvanya menjadi lebih curam. Hasil pemodelan inversi setelah dilakukan injeksi CO2 mempunyai kesalahan perhitungan yang cukup kecil yaitu kurang dari 5%. Meskipun mempunyai kesalahan yang kecil hasil yang diperoleh tidak sesuai dengan kondisi yang sebenarnya. Hasil yang tidak sesuai tersebut dikarenakan solusi metode SVD damped least square bukan merupakan solusi yang unik. Selain itu, pendekatan lokal yang digunakanpada metode inversi tersebut membuat nilai minimum yang diperoleh saat proses inversi merupakan nilai minimum lokal. Sehingga hasil yang diperoleh tidak bisa menunjukkan pengaruh data secara keseluruhan meskipun dengan nilai kesalahan perhitungan yang kecil. Secara umum hasil yang diperoleh dari prosesinversi tidak bisa diterima, akan tetapi dari masing-masing titik data dapat teramati adanya peningkatan resistitas reservoir dari 1 Ωm sampai 3 Ωm.]]>
<![CDATA[Studi Pemodelan Metode Time Domain Electromagnetic 3D untuk Model Homogen dan Berlapis ]]>
<![CDATA[Ida Bagus Suananda Yogi]]>;
<![CDATA[Warsa Warsa]]>
<![CDATA[ Jurnal Geofisika Vol 15 No 3 (2017): Jurnal Geofisika ]]>
Publisher : <![CDATA[Himpunan Ahli Geofisika Indonesia (HAGI) ]]>
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DOI: 10.36435/jgf.v15i1.16
<![CDATA[Makalah ini membahas pemodelan sintetik data time-domain electromagnetic (TDEM) 3D untuk model bumi berlapis homogen dan bersifat isotropis. Beberapa model 3D dan bumi berlapis sederhana digunakan dalam pemodelan untuk mengetahui respon model. Pemodelan dilakukan menggunakan metode beda hingga domin-waktu (nite dierence time-domain) secara 3D. Metode beda hingga domin-waktu merupakan metode yang cukup intuitif untuk dipahami karena mengikuti proses induksi medan elektromagnetik di alam. Hasil pemodelan menunjukkan bahwa semakin besar jarak transmitter-recevier, nilai arus yang diinjeksikan dan panjang transmitter, maka struktur dalam akan semakin mudah terdeteksi atau menghasilkan respon sinyal yang masih kuat. Fakta lain adalah bahwa nilai arus sangat berperan sebagai pengali nilai respon, termasuk panjang transmitter jika panjang transmitter tidak lebih besar dari jarak transmitter-receiver. Hasil lainnya adalah bahwa respon sinyal model bumi berlapis hasil pemodelan 1D serupa dengan hasil pemodelan 3D. Dari hasil pemodelan anomali balok secara 3D didapati bahwa dimensi lateral dari anomali balok mempengaruhi respon secara signikan. Namun, pemodelan 1D menghasilkan respon sinyal yang sama untuk model balok yang berbeda. Dari penelitian ini, dapat disimpulkan bahwa pemodelan 3D model homogen isotropis menggunakan parameter akuisisi yang berbeda dapat mempengaruhi intesitas dari respon sinyal yang berujung pada sensitivitas pengukuran untuk mendeteksi anomali tertentu. Hal lain yang perlu dicermati adalah anomali 3D dapat menghasilkan model yang berbeda pada pemodelan 1D dan 3D, sehingga dimensi struktur perlu diperkirakan dalam mengolah data TDEM.]]>
