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Record W2755299779 · doi:10.5539/ilr.v6n1p138

Horizontal Drilling of Crude Oil: A Challenge to the Norms of Property Rights

2017· article· en· W2755299779 on OpenAlexvenueno aff
Kato Gogo Kingston, Charity Olunma Kaniye-Ebeku

Bibliographic record

VenueInternational Law Research · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsnot available
Fundersnot available
KeywordsTrespassDirectional drillingDrillingPetroleum engineeringNatural resourceFossil fuelMineral resource classificationNatural resource economicsUnconventional oilProperty rightsBusinessMining engineeringGeologyEnvironmental scienceLawPolitical scienceGeochemistryEconomicsEngineeringMechanical engineeringWaste management

Abstract

fetched live from OpenAlex

Two altitudinal relationships propel current crude oil exploration jurisprudence and litigation namely: Surface land ownership and sub-surface rights (including mineral ownership). In the United States, the conflicts between the surface and mineral owners has theatrically increased in the last decade. Elsewhere, notably Nigeria, conflicts over land rights and the ownership of sub-surface minerals is yet to be fully resolved. Our goal herein is to explore the interaction between the law of property and the tort of trespass as applicable to the surface and subsurface exploration and extraction of crude oil and natural gas with specific focus on the scientific advances in horizontal drilling techniques widely used by the oil corporations in the various oil reservoirs across the world. Horizontal drilling is described in this paper, as the exercise of drilling for liquid and gaseous mineral resources by other means other than sinking vertical wells. We argue that, horizontal drilling is one of the easiest means by which governments could lawfully capture crude oil and gas from reservoirs of neighbouring nations to the extent that joint development agreement becomes unnecessary. Also, we opined that nations such as Nigeria could easily resolve issues of resources allocation by reducing the spread of surface wells. This could be achieved through the establishment of very few centralised drilling sites where slant or horizontal drilling can tap into various reservoirs thereby, eliminating the contestation of local agitators.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.960
Threshold uncertainty score0.887

Codex and Gemma teacher scores by category

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

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 head0.139
GPT teacher head0.339
Teacher spread0.200 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2017
Admission routes1
Has abstractyes

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