Research Article: Estimating decades-long trends in petroleum field energy return on investment (EROI) with an engineering-based model

Date Published: February 8, 2017

Publisher: Public Library of Science

Author(s): Vinay S. Tripathi, Adam R. Brandt, Vanesa Magar.


This paper estimates changes in the energy return on investment (EROI) for five large petroleum fields over time using the Oil Production Greenhouse Gas Emissions Estimator (OPGEE). The modeled fields include Cantarell (Mexico), Forties (U.K.), Midway-Sunset (U.S.), Prudhoe Bay (U.S.), and Wilmington (U.S.). Data on field properties and production/processing parameters were obtained from a combination of government and technical literature sources. Key areas of uncertainty include details of the oil and gas surface processing schemes. We aim to explore how long-term trends in depletion at major petroleum fields change the effective energetic productivity of petroleum extraction. Four EROI ratios are estimated for each field as follows: The net energy ratio (NER) and external energy ratio (EER) are calculated, each using two measures of energy outputs, (1) oil-only and (2) all energy outputs. In all cases, engineering estimates of inputs are used rather than expenditure-based estimates (including off-site indirect energy use and embodied energy). All fields display significant declines in NER over the modeling period driven by a combination of (1) reduced petroleum production and (2) increased energy expenditures on recovery methods such as the injection of water, steam, or gas. The fields studied had NER reductions ranging from 46% to 88% over the modeling periods (accounting for all energy outputs). The reasons for declines in EROI differ by field. Midway-Sunset experienced a 5-fold increase in steam injected per barrel of oil produced. In contrast, Prudhoe Bay has experienced nearly a 30-fold increase in amount of gas processed and reinjected per unit of oil produced. In contrast, EER estimates are subject to greater variability and uncertainty due to the relatively small magnitude of external energy investments in most cases.

Partial Text

This paper is adapted from the M.S. thesis of Tripathi for publication in PLOS ONE [1].

Historical operating statistics and reservoir parameters were obtained for each field to allow the use of OPGEE to estimate its EROI. If necessary, temporal data were converted to daily average rates for each year that a field was modeled. An example is the Alaska Oil and Gas Conservation Commission’s reporting of total monthly water production at Prudhoe Bay [16]. For a given year the total monthly water production was summed to obtain a yearly total and then divided by 365 to obtain a daily rate for that particular year.

This section contains overviews of data acquisition, assumptions, and extrapolations for the five fields. For the calculation of transport-related energy investment flows it is assumed that Houston, U.S. is the destination for oil from all five fields. This assumption provides a constant basis of comparison, following Brandt et al. [8].

Using OPGEE to estimate a field’s EROI is an approximate process involving the generalization of locally heterogeneous and uncertain reservoir parameters to field-level assessments. Furthermore, details regarding the surface processing of crude oil are not generally available.

All fields experienced substantial declines in estimated NER during their modeling periods. EER estimates were more varied. Four of the fields had moderate to severe EER declines. At Prudhoe Bay, the EERoil declined only moderately but the EERtotal increased over the modeling period. Within a field, the NER and EER ratios have very different profiles.

All five fields analyzed in this study exhibit significant declines in NER/EROI over time. The temporal declines in EROI estimates observed in this study result both from decreasing oil and gas production and increasing energy investments required for processing and handling fluids.




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