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Record W2061163478 · doi:10.2118/2005-264

Determination of Connate Water Salinity From Core

2005· article· en· W2061163478 on OpenAlexaboutno aff
C. Pan

Bibliographic record

VenueCanadian International Petroleum Conference · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality Monitoring Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsSalinityCore (optical fiber)GeologyPetroleum engineeringEnvironmental scienceComputer scienceOceanographyTelecommunications

Abstract

fetched live from OpenAlex

Abstract One of the parameters needed to calculate in-situ water saturation from wireline logs is the resistivity of connate water, Rw. It is usually determined by measuring the resistivity and chemical composition of uncontaminated connate water produced from the formation or underline aquifer. If the formation does not produce any connate water, e.g., Deep Basin plays in Western Canada and tight gas reservoirs, or the produced water is contaminated it is difficult to determine accurate Rw necessary for water saturation calculation. This paper presents the results of a laboratory study of examining the validity of core based salinity determination. Controlled experiments were conducted on core samples, one Berea sandstone core, one tight sandstone core and one tight carbonate core with the latter two coming from gas producing formations in Alberta. The air permeability of the samples varies from 1 mD to 80 mD. Standard sandstone brine and carbonate brine of known salinity and compositions were used as the base fluids for comparison in the tests. Several methods, i.e., electrical properties measurement (back calculating Rw), de-ionized water flow through extraction, methanol flow through extraction, and extraction of core salts by leaching ground core, are compared and the pros and cons of each method are discussed. All of the methods tested in the study provided reasonably good results for the sandstone samples with little soluble minerals but poor results for the carbonate sample due to soluble minerals in the matrix. The effect of dissolution of soluble minerals on extracted salinity and individual ion concentrations are evaluated. Introduction One of the parameters needed to calculate in-situ water saturation from wireline logs is the resistivity of connate water, Rw. It is usually determined by measuring the resistivity and chemical composition of uncontaminated connate water produced from the formation or underline aquifer. Log analysis using SP logs and interpretation from porosity and resistivity logs in aquifer are other possible sources of Rw values. If the formation does not produce any connate water, e.g., deep basin plays in Western Canada and tight gas reservoirs, or the produced water is contaminated it is difficult to determine accurate Rw necessary for water saturation calculation. Difficulty also arises if the salinity of connate water in a reservoir is not constant, leading to vertical and/or areal variation in Rw in the reservoir (McCoy, et al, 1994; Rathmell, et al., 1995; Rathmell, et al. 1999). In these cases core based salinity measurement provides an alternative and, sometimes, the only method to determine the Rw values. Accurate measurements of core water salinity are based on the assumption that all of the chemical ions in connate water at reservoir conditions are still contained and remained the same in the core water at ambient conditions at surface. If the formation water is not at or near the solubility limits, i.e., soluble at reservoir temperature and pressure but insoluble at ambient conditions, it is possible to cut cores that retain in-situ formation water compositions by low invasion coring technology and oil based mud (OBM).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.468
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0040.001

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 head0.043
GPT teacher head0.263
Teacher spread0.220 · 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.

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

Citations2
Published2005
Admission routes1
Has abstractyes

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