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Record W2083430731 · doi:10.4043/21645-ms

Resource Drilling of the Solwara 1 Seafloor Massive Sulfide (SMS) Deposit

2011· article· en· W2083430731 on OpenAlexaboutno aff
M. D. White, Anthony Manocchio, Jonathan Lowe, Mike Johnston, Tom Sant

Bibliographic record

VenueAll Days · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geophysical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDrillingGeologyRemotely operated vehicleSubseaDrillSeafloor spreadingRemotely operated underwater vehicleScientific drillingOceanographyMining engineeringEngineeringComputer scienceMechanical engineeringRobot

Abstract

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Abstract Nautilus Minerals is the world leader in exploration and development of deep ocean seafloor massive sulphide (SMS) resources. The company is currently focused on generating its resource pipeline in the Western Pacific and its first development project for recovery of high-grade copper, gold and silver mineralisation from its Solwara 1 site in the Bismarck Sea, Papua New Guinea. The Solwara 1 site is located at a water depth of 1,600 - 1800 meters. Over 150 SMS seafloor surface samples have been collected from chimney structures during dives made by remote operated vehicles (ROVs). In order to obtain an understanding of the sub-surface mineralisation, Nautilus carried out 3 drilling programs between 2006 and 2008 which allowed the calculation of a Canadian NI43-101 compliant resource estimate. The initial 2006 campaign was based on conventional offshore surface driven drill equipment. In conjunction with the subsea remote technology industry, Nautilus subsequently developed an ROV operated seafloor drill system with improved drill core recovery and efficiency. This technology was developed further with a 2010 drill program to increase the available geological knowledge at Solwara 1 and adjacent prospects. This paper will provide an overview of Nautilus' SMS drilling requirements and recap the evolution of drilling technology and operations undertaken at Solwara 1 from 2006 to 2010. The paper will also discuss the potential of further developments in drilling techniques and equipment to increase or improve drilling depth, efficiency and data quality. Introduction Nautilus Minerals is a leader in the exploration and development of Seafloor Massive Sulphide (SMS) systems. These high grade copper, gold and zinc deposits are considered to be modern analogues of ancient volcanogenic massive sulphide (VMS) deposits. In the western Pacific, Nautilus Minerals is predominantly engaged in exploration for SMS systems in the territorial waters of Papua New Guinea and the 1887 Proclamation Area of Tonga. Nautilus Minerals development plan is to commence production at its Solwara 1 site located within Mining Lease (ML) 154 in the Bismarck Sea, Papua New Guinea. As of January 2011, the Solwara 1 prospect has a NI 43-101 compliant indicated and inferred mineral resource estimate of 870 kT and 1,300 kT respectively. SMS systems are typically located in water depths greater than 1,000 metres and in close proximity to tectonic plate boundaries and submarine volcanic activity. Cold seawater which has entered the earth's crust is heated to high temperatures by volcanic and magmatic processes, forming hot hydrothermal fluids, which can become rich in economic metal concentrations. These hot fluids are driven to the seafloor by convection, producing hydrothermal plumes or " black smokers??. SMS systems are formed by the precipitation of metal bearing sulphide minerals as chimneys, which range from mere decimetres to a few metres in diameter and can reach up to 20 metres in height. The continued process of chimney build-up, extinction, renewal and collapse can lead to the formation of sulphide mounds, which can be hundreds of metres in lateral extent (Figure 1).

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.031
GPT teacher head0.185
Teacher spread0.154 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2011
Admission routes1
Has abstractyes

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