TY - CHAP AU - Abordán, Armand AU - Szabó, Norbert Péter ED - Szabó, Norbert Péter ED - Virág, Zoltán István TI - Joint Optimization of Factor Scores and Loadings by Particle Swarm Optimization T2 - Új eredmények a műszaki föld- és környezettudományban 2022 PB - Miskolci Egyetem, Műszaki Földtudományi Kar CY - Miskolc-Egyetemváros SN - 9789633582695 PY - 2022 SP - 139 EP - 148 PG - 10 UR - https://m2.mtmt.hu/api/publication/33315458 ID - 33315458 LA - English DB - MTMT ER - TY - JOUR AU - Szabó, Norbert Péter AU - Abordán, Armand AU - Dobróka, Mihály TI - Permeability extraction from multiple well logs using particle swarm optimization based factor analysis JF - GEM - INTERNATIONAL JOURNAL ON GEOMATHEMATICS J2 - GEM - INT J GEOMATHEMATICS VL - 13 PY - 2022 IS - 1 PG - 27 SN - 1869-2672 DO - 10.1007/s13137-022-00200-x UR - https://m2.mtmt.hu/api/publication/32966199 ID - 32966199 AB - In this paper, we present an innovative factor analysis algorithm for hydrocarbon exploration to estimate the intrinsic permeability of reservoir rocks from well logs. Unlike conventional evaluation methods that employ a single or a limited number of data types, we process simultaneously all available data to derive the first statistical factor and relate it to permeability by regression analysis. For solving the problem of factor analysis, we introduce an improved particle swarm optimization method, which searches for the global minimum of the distance between the observed and calculated data and gives a quick estimation for the factor scores. The learning factors of the intelligent computational technique such as the cognitive and social constants are specified as hyperparameters and calculated by using simulated annealing algorithm as heuristic hyperparameter estimator. Instead of the arbitrary fixation of these hyperparameters, we refine them in an iterative process to give reliable estimation both for the statistical factors and formation permeability. The estimated learning parameters are consistent with literature recommendations. We demonstrate the feasibility of the proposed well-log analysis method by a Hungarian oilfield study involving open-hole wireline logs and core data. We determine the spatial distribution of permeability both along a borehole and between more wells using the factor analysis approach, which serves as efficient and reliable multivariate statistical tool for advanced formation evaluation and reservoir modeling. LA - English DB - MTMT ER - TY - JOUR AU - Abordán, Armand AU - Szabó, Norbert Péter TI - Machine learning based approach for the interpretation of engineering geophysical sounding logs JF - ACTA GEODAETICA ET GEOPHYSICA J2 - ACTA GEOD GEOPHYS VL - 56 PY - 2021 IS - 4 SP - 681 EP - 696 PG - 16 SN - 2213-5812 DO - 10.1007/s40328-021-00354-4 UR - https://m2.mtmt.hu/api/publication/32147491 ID - 32147491 N1 - K-135323 sz. OTKA AB - In this paper, a set of machine learning (ML) tools is applied to estimate the water saturation of shallow unconsolidated sediments at the Bátaapáti site in Hungary. Water saturation is directly calculated from the first factor extracted from a set of direct push logs by factor analysis. The dataset observed by engineering geophysical sounding tools as special variants of direct-push probes contains data from a total of 12 shallow penetration holes. Both one- and two-dimensional applications of the suggested method are presented. To improve the performance of factor analysis, particle swarm optimization (PSO) is applied to give a globally optimized estimate for the factor scores. Furthermore, by a hyperparameter estimation approach, some control parameters of the utilized PSO algorithm are automatically estimated by simulated annealing (SA) to ensure the convergence of the procedure. The result of the suggested ML-based log analysis method is compared and verified by an independent inversion estimate. The study shows that the PSO-based factor analysis aided by hyperparameter estimation provides reliable in situ estimates of water saturation, which may improve the solution of environmental end engineering problems in shallow unconsolidated heterogeneous formations. LA - English DB - MTMT ER - TY - GEN AU - Abordán, Armand AU - Szabó, Norbert Péter TI - Tárolókőzetek áteresztőképességének meghatározása hiperparaméter becsléssel támogatott PSO eljárással PY - 2020 UR - https://m2.mtmt.hu/api/publication/31970938 ID - 31970938 N1 - Előadás LA - Hungarian DB - MTMT ER - TY - CONF AU - Somogyiné Molnár, Judit AU - Abordán, Armand AU - Dobróka, Tünde Edit AU - Ormos, Tamás AU - Dobróka, Mihály TI - Characteristic Pressure Spectrum Produced with a New Multi-Exponential Model Describing Quality Factor-Pressure Relationship T2 - NSG2020 26th European Meeting of Environmental and Engineering Geophysics PY - 2020 PG - 4 DO - 10.3997/2214-4609.202020074 UR - https://m2.mtmt.hu/api/publication/31847576 ID - 31847576 LA - English DB - MTMT ER - TY - THES AU - Abordán, Armand TI - Global Optimization-based Data Processing Methods for Advanced Well Logging Applications PY - 2020 SP - 70 DO - 10.14750/ME.2020.007 UR - https://m2.mtmt.hu/api/publication/31605657 ID - 31605657 N1 - "A cikkben/előadásban/tanulmányban ismertetett kutató munka az EFOP-3.6.1-16-00011 jelű „Fiatalodó és Megújuló Egyetem – Innovatív Tudásváros – a Miskolci Egyetem intelligens szakosodást szolgáló intézményi fejlesztése” projekt részeként – a Széchenyi 2020 keretében – az Európai Unió támogatásával, az Európai Szociális Alap társfinanszírozásával valósul meg" = “The described article/presentation/study was carried out as part of the EFOP-3.6.1-16-00011 “Younger and Renewing University – Innovative Knowledge City – institutional development of the University of Miskolc aiming at intelligent specialisation” project implemented in the framework of the Szechenyi 2020 program. The realization of this project is supported by the European Union, co-financed by the European Social Fund.” LA - English DB - MTMT ER - TY - JOUR AU - Abordán, Armand AU - Szabó, Norbert Péter TI - Uncertainty reduction of interval inversion estimation results using a factor analysis approach JF - GEM - INTERNATIONAL JOURNAL ON GEOMATHEMATICS J2 - GEM - INT J GEOMATHEMATICS VL - 11 PY - 2020 IS - 1 PG - 17 SN - 1869-2672 DO - 10.1007/s13137-020-0144-4 UR - https://m2.mtmt.hu/api/publication/31203354 ID - 31203354 LA - English DB - MTMT ER - TY - CHAP AU - Abordán, Armand ED - Hatvani, István Gábor ED - Tanos, Péter ED - Fedor, Ferenc TI - Reducing the uncertainty of parameter estimation for the interval inversion method using factor analysis T2 - GEOMATES 2019. International Congress on Geomathematics in Earth-& Environmental Sciences PB - Regional Committee of the Hungarian Academy of Sciences at Pécs CY - Pécs SN - 9789637068119 PY - 2019 SP - 49 UR - https://m2.mtmt.hu/api/publication/32079439 ID - 32079439 LA - English DB - MTMT ER - TY - JOUR AU - Abordán, Armand AU - Szabó, Norbert Péter TI - Selecting control parameters for the practicle swarm optimization based factor analysis JF - MŰSZAKI FÖLDTUDOMÁNYI KÖZLEMÉNYEK J2 - MŰSZAKI FÖLDTUDOMÁNYI KÖZLEMÉNYEK VL - 88 PY - 2019 IS - 1 SP - 134 EP - 140 PG - 7 SN - 2063-5508 UR - https://m2.mtmt.hu/api/publication/30774076 ID - 30774076 LA - English DB - MTMT ER - TY - CHAP AU - Abordán, Armand ED - Szabó, Norbert Péter ED - Papp, Richárd Zoltán TI - Local inversion of direct push logging data by invasive weed optimization T2 - Doktoranduszok Fóruma PB - Miskolci Egyetem CY - Miskolc SN - 9789633581964 PY - 2019 SP - 3 EP - 9 PG - 7 UR - https://m2.mtmt.hu/api/publication/30754476 ID - 30754476 N1 - "A cikkben/előadásban/tanulmányban ismertetett kutató munka az EFOP-3.6.1-16-00011 jelű „Fiatalodó és Megújuló Egyetem – Innovatív Tudásváros – a Miskolci Egyetem intelligens szakosodást szolgáló intézményi fejlesztése” projekt részeként – a Széchenyi 2020 keretében – az Európai Unió támogatásával, az Európai Szociális Alap társfinanszírozásával valósul meg" = “The described article/presentation/study was carried out as part of the EFOP-3.6.1-16-00011 “Younger and Renewing University – Innovative Knowledge City – institutional development of the University of Miskolc aiming at intelligent specialisation” project implemented in the framework of the Szechenyi 2020 program. The realization of this project is supported by the European Union, co-financed by the European Social Fund.” AB - Műszaki Földtudományi Kar Szekciókiadványa LA - English DB - MTMT ER -