An interactive sequential-decision benchmark from geosteering

During drilling, to maximize future expected production of hydrocarbon resources, the experts commonly adjust the trajectory (geosteer) in response to new insights obtained through real-time measurements. Geosteering workflows are increasingly based on the quantification of subsurface uncertainties...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Sergey Alyaev, Sofija Ivanova, Andrew Holsaeter, Reidar Brumer Bratvold, Morten Bendiksen
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Interactive benchmark Sequential geosteering decisions Uncertainty quantification Expert decisions Experimental study Decision support system Geography. Anthropology. Recreation G Geology QE1-996.5 Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/7e195f0452f441f0b7d2f698d46c25c9
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:7e195f0452f441f0b7d2f698d46c25c9
record_format	dspace
spelling	oai:doaj.org-article:7e195f0452f441f0b7d2f698d46c25c92021-11-12T04:47:12ZAn interactive sequential-decision benchmark from geosteering2590-197410.1016/j.acags.2021.100072https://doaj.org/article/7e195f0452f441f0b7d2f698d46c25c92021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2590197421000203https://doaj.org/toc/2590-1974During drilling, to maximize future expected production of hydrocarbon resources, the experts commonly adjust the trajectory (geosteer) in response to new insights obtained through real-time measurements. Geosteering workflows are increasingly based on the quantification of subsurface uncertainties during real-time operations. As a consequence, operational decision-making is becoming both better informed and more complex. This paper presents an experimental web-based decision support system, which can be used to both teach expert decisions under uncertainty or further develop decision optimization algorithms in a controlled environment. A user of the system (either human or AI) controls the decisions to steer the well or stop drilling. Whenever a user drills ahead, the system produces simulated measurements along the selected well trajectory which are used to update the uncertainty represented by model realizations using the ensemble Kalman filter. To enable informed decisions the system is equipped with functionality to evaluate the value of the selected trajectory under uncertainty with respect to the objectives of the current experiment.To illustrate the utility of the system as a benchmark, we present the initial experiment, in which we compare the decision skills of geoscientists with those of a recently published automatic decision support algorithm. The experiment and the survey after it showed that most participants were able to use the interface and complete the three test rounds. At the same time, the automated algorithm outperformed 28 out of 29 human participants.Such an experiment is not sufficient to draw conclusions about practical geosteering but is nevertheless useful for geoscience. First, this communication-by-doing made 76% of respondents more curious about and/or confident in the presented technologies. Second, the system can be further used as a benchmark for sequential decisions under uncertainty. This can accelerate development of algorithms and improve the training for decision making.Sergey AlyaevSofija IvanovaAndrew HolsaeterReidar Brumer BratvoldMorten BendiksenElsevierarticleInteractive benchmarkSequential geosteering decisionsUncertainty quantificationExpert decisionsExperimental studyDecision support systemGeography. Anthropology. RecreationGGeologyQE1-996.5Electronic computers. Computer scienceQA75.5-76.95ENApplied Computing and Geosciences, Vol 12, Iss , Pp 100072- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Interactive benchmark Sequential geosteering decisions Uncertainty quantification Expert decisions Experimental study Decision support system Geography. Anthropology. Recreation G Geology QE1-996.5 Electronic computers. Computer science QA75.5-76.95
spellingShingle	Interactive benchmark Sequential geosteering decisions Uncertainty quantification Expert decisions Experimental study Decision support system Geography. Anthropology. Recreation G Geology QE1-996.5 Electronic computers. Computer science QA75.5-76.95 Sergey Alyaev Sofija Ivanova Andrew Holsaeter Reidar Brumer Bratvold Morten Bendiksen An interactive sequential-decision benchmark from geosteering
description	During drilling, to maximize future expected production of hydrocarbon resources, the experts commonly adjust the trajectory (geosteer) in response to new insights obtained through real-time measurements. Geosteering workflows are increasingly based on the quantification of subsurface uncertainties during real-time operations. As a consequence, operational decision-making is becoming both better informed and more complex. This paper presents an experimental web-based decision support system, which can be used to both teach expert decisions under uncertainty or further develop decision optimization algorithms in a controlled environment. A user of the system (either human or AI) controls the decisions to steer the well or stop drilling. Whenever a user drills ahead, the system produces simulated measurements along the selected well trajectory which are used to update the uncertainty represented by model realizations using the ensemble Kalman filter. To enable informed decisions the system is equipped with functionality to evaluate the value of the selected trajectory under uncertainty with respect to the objectives of the current experiment.To illustrate the utility of the system as a benchmark, we present the initial experiment, in which we compare the decision skills of geoscientists with those of a recently published automatic decision support algorithm. The experiment and the survey after it showed that most participants were able to use the interface and complete the three test rounds. At the same time, the automated algorithm outperformed 28 out of 29 human participants.Such an experiment is not sufficient to draw conclusions about practical geosteering but is nevertheless useful for geoscience. First, this communication-by-doing made 76% of respondents more curious about and/or confident in the presented technologies. Second, the system can be further used as a benchmark for sequential decisions under uncertainty. This can accelerate development of algorithms and improve the training for decision making.
format	article
author	Sergey Alyaev Sofija Ivanova Andrew Holsaeter Reidar Brumer Bratvold Morten Bendiksen
author_facet	Sergey Alyaev Sofija Ivanova Andrew Holsaeter Reidar Brumer Bratvold Morten Bendiksen
author_sort	Sergey Alyaev
title	An interactive sequential-decision benchmark from geosteering
title_short	An interactive sequential-decision benchmark from geosteering
title_full	An interactive sequential-decision benchmark from geosteering
title_fullStr	An interactive sequential-decision benchmark from geosteering
title_full_unstemmed	An interactive sequential-decision benchmark from geosteering
title_sort	interactive sequential-decision benchmark from geosteering
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/7e195f0452f441f0b7d2f698d46c25c9
work_keys_str_mv	AT sergeyalyaev aninteractivesequentialdecisionbenchmarkfromgeosteering AT sofijaivanova aninteractivesequentialdecisionbenchmarkfromgeosteering AT andrewholsaeter aninteractivesequentialdecisionbenchmarkfromgeosteering AT reidarbrumerbratvold aninteractivesequentialdecisionbenchmarkfromgeosteering AT mortenbendiksen aninteractivesequentialdecisionbenchmarkfromgeosteering AT sergeyalyaev interactivesequentialdecisionbenchmarkfromgeosteering AT sofijaivanova interactivesequentialdecisionbenchmarkfromgeosteering AT andrewholsaeter interactivesequentialdecisionbenchmarkfromgeosteering AT reidarbrumerbratvold interactivesequentialdecisionbenchmarkfromgeosteering AT mortenbendiksen interactivesequentialdecisionbenchmarkfromgeosteering
_version_	1718431238856900608

An interactive sequential-decision benchmark from geosteering

Ejemplares similares