Imaging the magmatic system beneath the Krafla geothermal field, Iceland: A new 3-D electrical resistivity model from inversion of magnetotelluric data
Bibliographic record
Abstract
SUMMARY Krafla is an active volcanic field and a high-temperature geothermal system in northeast Iceland. As part of a program to produce more energy from higher temperature wells, the IDDP-1 well was drilled in 2009 to reach supercritical fluid conditions below the Krafla geothermal field. However, drilling ended prematurely when the well unexpectedly encountered rhyolite magma at a depth of 2.1 km. In this paper we re-examine the magnetotelluric (MT) data that were used to model the electrical resistivity structure at Krafla. We present a new 3-D resistivity model that differs from previous inversions due to (1) using the full impedance tensor data and (2) a finely discretized mesh with horizontal cell dimensions of 100 m by 100 m. We obtained similar resistivity models from using two different prior models: a uniform half-space, and a previously published 1-D resistivity model. Our model contains a near-surface resistive layer of unaltered basalt and a low resistivity layer of hydrothermal alteration (C1). A resistive region (R1) at 1 to 2 km depth corresponds to chlorite-epidote alteration minerals that are stable at temperatures of about 220 to 500 °C. A low resistivity feature (C2) coincides with the Hveragil fault system, a zone of increased permeability allowing interaction of aquifer fluids with magmatic fluids and gases. Our model contains a large, low resistivity zone (C3) below the northern half of the Krafla volcanic field that domes upward to a depth of about 1.6 km b.s.l. C3 is partially coincident with reported low S-wave velocity zones which could be due to partial melt or aqueous fluids. The low resistivity could also be attributed to dehydration and decomposition of chlorite and epidote that occurs above 500 °C. As opposed to previously published resistivity models, our resistivity model shows that IDDP-1 encountered rhyolite magma near the upper edge of C3, where it intersects C2. In order to assess the sensitivity of the MT data to melt at the bottom of IDDP-1, we added hypothetical magma bodies with resistivities of 0.1 to 30 Ωm to our resistivity model and compared the synthetic MT data to the original inversion response. We used two methods to compare the MT data fit: (1) the change in r.m.s. misfit and (2) an asymptotic p-value obtained from the Kolmogorov–Smirnov (K–S) statistical test on the two sets of data residuals. We determined that the MT data can only detect sills that are unrealistically large (2.25 km3) with very low resistivities (0.1 or 0.3 Ωm). Smaller magma bodies (0.125 and 1 km3) were not detected; thus the MT data are not sensitive to small rhyolite magma bodies near the bottom of IDDP-1. Our tests gave similar results when evaluating the changes in r.m.s. misfit and the K–S test p-values, but the K–S test is a more objective method than appraising a relative change in r.m.s. misfit. Our resistivity model and resolution tests are consistent with the idea of rhyolite melt forming by re-melting of hydrothermally altered basalt on the edges of a deeper magma body.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".