Data-based support for petroleum prospect evaluation
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RESEARCH ARTICLE
Data-based support for petroleum prospect evaluation Summaya Mumtaz1
· Irina Pene1 · Adnan Latif1 · Martin Giese1
Received: 23 March 2020 / Accepted: 10 August 2020 © The Author(s) 2020
Abstract We consider the challenging task of evaluating the commercial viability of hydrocarbon prospects based on limited information, and in limited time. We investigate purely data-driven approaches to predicting key reservoir parameters and obtain a negative result: the information that is typically available for prospect evaluation and is suitable for data-based methods, cannot be used for the required predictions. We can show however that the same information is sufficient to produce a limited list of potentially similar well-explored reservoirs (known as analogues) that can support the prospect evaluation work of human geoscientists. We base the proposal of analogues on similarity measures on the data available about prospects. Technically, the challenge is to define suitable similarity measures on categorical data like depositional environment or rock types. Existing data-based similarity measures for categorical data do not perform well, since they do not take geological domain knowledge into account. We propose two novel similarity measures that use domain knowledge in the form of hierarchies on categorical values. Comparative evaluation shows that the semantic-based similarity measures outperform the existing data-driven approaches and are effective in comparison to the human analogue selection. Keywords Analogues · Prediction · Similarity · Machine learning
Introduction One of the challenging tasks of commercial hydrocarbon exploration is that of prospect evaluation: a limited amount of information is available for a given location (the prospect). Based on substantial knowledge of previously explored petroleum reservoirs, one has to determine whether it will be worth investing in the further development of the prospect. The usual method employed by geoscientists for prospect evaluation is based on analogues: a number of wellexplored reservoirs are considered that share as many of Communicated by: H. Babaie Summaya Mumtaz
[email protected] Irina Pene [email protected] Adnan Latif [email protected] Martin Giese [email protected] 1
SIRIUS Center for Scalable Data Access, University of Oslo, Gaustadall´een 23B, 0373 Oslo, Norway
the given properties of the prospect as possible. These analogues are used (together with the available information about the prospect) to give estimates and uncertainty bounds for key parameters such as reservoir porosity, permeability, and size. The viability of the prospect is then determined from these parameters. Prospect evaluation using analogues is challenging for a number of reasons: 1. the information about the prospect is often rather limited, which means that it is hard to say how good analogues really are, and therefore predictions will be very uncertain 2. the time available for prospect evaluation is also limited, so that it is not possible to reliably find
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