Maxime Catinat1,2<\/sup> Benjamin Brigaud1<\/sup>, Miklos Antics2<\/sup><\/p>\n\n\n\n 1<\/sup>Universit\u00e9 Paris-Saclay, GEOPS, CNRS, 91405 Orsay, France<\/p>\n\n\n\n 2<\/sup>GEOFLUID, 165 Rue de la belle \u00e9toile, 95700 Roissy CDG, France<\/p>\n\n\n\n 3<\/sup>IFP Energies Nouvelles, 1-4 Avenue de bois pr\u00e9au, 92852 Rueil-Malmaison, France<\/p>\n\n\n\n 4<\/sup>BRGM, 3 Avenue Claude Guillemin, 45100 Orl\u00e9ans<\/p>\n\n\n\n 5<\/sup>Universit\u00e9 Paris-Saclay, CNRS, CEA, UVSQ, Laboratoire des Sciences du Climat et de l\u2019Environnement, 91191, Gif-sur-Yvette, France<\/p>\n\n\n\n With around 50 heating networks today operating, the aera around Paris is the European region which concentrates the most heating network production units in terms of deep geothermal energy. In France, the energy-climate strategy plans to produce 6.4TWh in 2023, compared to 1.5TWh produced in 2016 [1]. Despite an exceptional geothermal potential, the current average development rate of 70MWh\/year will not allow this objective to be achieved, it would be necessary to reach a rate of 6 to 10 times higher. The optimization of the use of deep geothermal energy is a major challenge for France, and in Ile-de-France, which has a population of nearly 12 million inhabitants. This project aims to reconstruct and simulate heat flows in the Paris Basin using an innovative methodology (1) to characterize, predict and model the properties of reservoirs (facies, porosity, permeability) and (2) simulate future circulations and predict the performance at a given location (sedimentary basin) on its geothermal potential. This study focuses on a high density area of well infrastructures around Cachan, (8 doublets, 1 triplet in 56 km2). A new sub-horizontal doublet concept has been recently (2017) drilled at Cachan to enhance heat exchange in medium to low permeability formations [2]. Nuclear Magnetic Resonance (NMR T2) logs have been recorded in the sub-horizontal well (GCAH2) providing information on pore size distribution or permeability. We integrated all logging data (gamma ray, density, resistivity, sonic, NRM T2) of the 19 wells in the area and 120 thin section observations from cuttings to derive a combined electrofacies-sedimentary facies description. A total of 10 facies is grouped into 5 facies associations coded in all the 19 wells according to depths and 10 3rd order stratigraphic sequences are recognized. The cell size of the 3D grid was set to 50 m x 50 m for the XY dimensions. The Z-size depends on the thickness of the sub-zones, averaging 5 m. The resulting 3D grid is composed of a total of nearly 800 000 cells. After upscaled, facies and stratigraphic surfaces are used to create a reliable model using the \u201cTruncated Gaussian With Trends\u201d algorithm. The petrophysical distribution \u201cGaussian Random Function Simulation\u201d is used to populate the entire grid with properties, included 2000 NMR data, considering each facies independently. The best reservoir is mainly located in the shoal deposits oolitic grainstones with average porosity of 12.5% and permeability of 100 mD. Finally, hydrodynamic and thermal simulations have been performed using Pumaflow to give information on the potential risk of interference between the doublets in the area and advices are given in the well trajectory to optimize the connectivity and the lifetime of the system. NMR data, especially permeability, allow to greater improve the simulations, defining time probabilities of thermal breakthrough in an area of high density wells.<\/p>\n\n\n\n R\u00e9f\u00e9rence<\/strong><\/p>\n\n\n\n [1] Minist\u00e8re de la Transition \u00e9cologique et solidaire, Strat\u00e9gie Fran\u00e7aise pour l\u2019\u00e9nergie et le climat, Programmation pluriannuelle de l\u2019\u00e9nergie. 2019.<\/p>\n\n\n\n [2] Wielemaker, E. Cavalleri, C., Dahlhaus, L., Reynaldos A., Sosio,G., Ungemach, P., Antics, M., Davaux, M., 2020. Delineating the geothermal structure and flow properties in a sub-horizontal well with the use of wireline and LWD data in a multiphysics approach. SPWLA 61st Annual Logging Symposium<\/p>\n\n\n\n Hadrien Thomas1<\/sup>, Benjamin Brigaud1<\/sup>, Hermann Zeyen1<\/sup>, Bertrand Saint-Bezar1<\/sup>, Thomas Blaise1<\/sup>, Elodie Zordan2<\/sup>, Simon Andrieu3<\/sup>, Beno\u00eet Vincent4<\/sup>, Eric Portier5<\/sup>, Emmanuel Mouche6<\/sup>, Hugo Chirol1<\/sup><\/p>\n\n\n\n 1<\/sup>Universit\u00e9 Paris-Saclay, CNRS, GEOPS, 91405, Orsay, France<\/p>\n\n\n\n 2<\/sup>Schlumberger, Software Integrated Solutions, Le Palatin 1, 1, Cours du Triangle, 92 936, La D\u00e9fense, Cedex, France<\/p>\n\n\n\n 3<\/sup>BRGM, 3 Avenue Claude Guillemin, BP 36009, 45060, Orl\u00e9ans, France<\/p>\n\n\n\n 4<\/sup>Cambridge Carbonate Ltd., 1 rue de Varoux, 21120, Marey-sur-Tille, France<\/p>\n\n\n\n 5<\/sup>CV Associ\u00e9s Engineering, 7 Chemin de la Marouette, 64100, Bayonne, France<\/p>\n\n\n\n 6<\/sup>Universit\u00e9 Paris-Saclay, CNRS, CEA, UVSQ, Laboratoire des sciences du Climat et de l\u2019environnement, 91191, Gif-sur-Yvette, France<\/p>\n\n\n\n Une acquisition par drone \u00e9quip\u00e9 d\u2019un appareil photo haute r\u00e9solution (12 Mpix) g\u00e9or\u00e9f\u00e9renc\u00e9e, associ\u00e9e avec les techniques de photogramm\u00e9trie, a permis de r\u00e9aliser une mod\u00e9lisation 3D virtuelle d\u2019un affleurement de roches calcaires avec une pr\u00e9cision centim\u00e9trique. Celui-ci est ainsi rapidement \u00ab transportable \u00bb au laboratoire, et permet de localiser les \u00e9chantillons pr\u00e9lev\u00e9s, la lev\u00e9e de logs suppl\u00e9mentaires, une cartographique compl\u00e8te et la corr\u00e9lation des faci\u00e8s observ\u00e9s sur le terrain. Des donn\u00e9es compl\u00e9mentaires peuvent \u00eatre extraites telles que des mesures de fractures ou de pendages (exemple ici : https:\/\/skfb.ly\/6RYGF<\/a>). A titre d\u2019exemple, les calcaires du Bathonien de la carri\u00e8re de Massangis (Bourgogne) ont \u00e9t\u00e9 investigu\u00e9s avec cette technique. La carri\u00e8re couvre une superficie de 0,4 km2<\/sup> et a longtemps \u00e9t\u00e9 consid\u00e9r\u00e9e comme un analogue \u00e0 l\u2019affleurement du r\u00e9servoir g\u00e9othermique de l\u2019Oolithe Blanche, r\u00e9servoir situ\u00e9 \u00e0 environ 1500 m de profondeur en r\u00e9gion parisienne. Dans notre cas d\u2019\u00e9tude, le mod\u00e8le de la carri\u00e8re de Massangis repr\u00e9sente un bon analogue pour repr\u00e9senter un r\u00e9servoir microporeux et\/ou domin\u00e9 par une porosit\u00e9 secondaire associ\u00e9e \u00e0 la d\u00e9dolomitisation. Les espaces poreux rhombo\u00e9driques de type moldique associ\u00e9s \u00e0 la d\u00e9dolomitisation sont bien exprim\u00e9s au sein de tr\u00e8s grandes dunes sous-marines de 15 \u00e0 20 m de hauteur. La photogramm\u00e9trie par drone combin\u00e9e \u00e0 l\u2019utilisation du G\u00e9omodeleur Petrel\u00ae est utilis\u00e9e pour cr\u00e9er un mod\u00e8le g\u00e9ologique qui reproduit fid\u00e8lement l\u2019architecture des faci\u00e8s observ\u00e9s dans la carri\u00e8re. La photogramm\u00e9trie par drone peut \u00eatre combin\u00e9e avec des travaux de terrain pour d\u00e9crire et localiser les faci\u00e8s et ainsi contraindre la distribution spatiale des propri\u00e9t\u00e9s p\u00e9trophysiques. Elle permet \u00e9galement de contraindre les formes des corps r\u00e9servoir dans une grille fine (XYZ = 1 m x 1 m x 0.5 m) pour des mod\u00e8les g\u00e9ologiques statiques plus r\u00e9alistes. Cette m\u00e9thodologie rapide va aider \u00e0 fournir des mod\u00e8les p\u00e9trophysiques 3D, de l\u2019\u00e9chelle microm\u00e9trique (pore) \u00e0 kilom\u00e9trique, \u00e0 partir d\u2019analogue d\u2019affleurement pour les r\u00e9servoirs g\u00e9othermiques.<\/p>\n\n\n\n Retrouvez les 2 pr\u00e9sentations effectu\u00e9es lors de la journ\u00e9e scientifique du Groupe Fran\u00e7ais d’\u00e9tude du Jurassique le 10 d\u00e9cembre 2020. NMR contribution in sub-horizontal well for porosity-permeability heterogeneity characterization in limestones: implications for 3D reservoir prediction and flow simulation in a world class geothermal aquifer Maxime Catinat1,2 Benjamin Brigaud1, Miklos Antics2 1Universit\u00e9 Paris-Saclay, GEOPS, CNRS, […]<\/p>\n","protected":false},"author":1,"featured_media":218,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[29],"tags":[45,41,46],"class_list":["post-217","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-meeting","tag-geothermal","tag-jurassic","tag-limestones","post-preview"],"yoast_head":"\n![\"\"](\"http:\/\/hebergement.universite-paris-saclay.fr\/upgeo\/wp-content\/uploads\/2020\/12\/Capture-de\u0301cran-2020-12-27-a\u0300-15.00.07.png\")
<\/a><\/figure>\n\n\n\nContribution de la photogramm\u00e9trie par drone \u00e0 la mod\u00e9lisation 3D des h\u00e9t\u00e9rog\u00e9n\u00e9it\u00e9s des r\u00e9servoirs carbonat\u00e9s (carri\u00e8re de Massangis, Bassin de Paris)<\/strong><\/h2>\n\n\n\n
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