Design and Implementation of a Scalable, Automated, Semi-Permanent Seismic Array for Detecting CO2 Extent during Geologic CO2 Injection

A proof-of-concept demonstration using a scalable, automated, semipermanent, seismic array (SASSA) is being conducted to test a novel seismic method for detecting and tracking an injected CO2plume as it traverses discreet points within a reservoir in southeastern Montana at Bell Creek oil field which is undergoing commercial CO2enhanced oil recovery (EOR). This document serves to describe the technical design of the project infrastructure, the operational approach, corresponding data collection, and data-processing activities

CO2 Enhanced Oil Recovery Life Cycle Analysis Model (Rev. 2)

In “How green is my oil?” by Azzolina et al., the authors presented an integrated life-cycle model for CO2-EOR where the CO2 is sourced from a coal-fired power plant. The model was developed entirely in Microsoft Excel® to improve transparency and provide a useful tool for other practitioners. This model is an updated version of the model from the article. The cells have been unlocked so they can be modified. Azzolina, N.A., Peck, W.D., Hamling, J.A., Gorecki, C.D., Ayash, S.C., Doll, T.E., Nakles, D.V., and Melzer, L.S., 2016, How green is my oil? a detailed look at greenhouse gas accounting for CO2-enhanced oil recovery (CO2-EOR) sites: International Journal of Greenhouse Gas Control, v. 51, p. 369–379. DOI: /10.1016/j.ijggc.2016.06.008. Acknowledgment: This material is based upon work supported by the U.S. Department of Energy National Energy Technology Laboratory under Award Number DE-FC26-05NT42592.https://commons.und.edu/eerc-publications/1000/thumbnail.jp

Systematic review with meta-analysis of the epidemiological evidence relating FEV₁ decline to lung cancer risk

<p>Abstract</p> <p>Background</p> <p>Reduced FEV₁ is known to predict increased lung cancer risk, but previous reviews are limited. To quantify this relationship more precisely, and study heterogeneity, we derived estimates of β for the relationship RR(diff) = exp(βdiff), where diff is the reduction in FEV₁ expressed as a percentage of predicted (FEV₁%P) and RR(diff) the associated relative risk. We used results reported directly as β, and as grouped levels of RR in terms of FEV₁%P and of associated measures (e.g. FEV₁/FVC).</p> <p>Methods</p> <p>Papers describing cohort studies involving at least three years follow-up which recorded FEV₁ at baseline and presented results relating lung cancer to FEV₁ or associated measures were sought from Medline and other sources. Data were recorded on study design and quality and, for each data block identified, on details of the results, including population characteristics, adjustment factors, lung function measure, and analysis type. Regression estimates were converted to β estimates where appropriate. For results reported by grouped levels, we used the NHANES III dataset to estimate mean FEV₁%P values for each level, regardless of the measure used, then derived β using regression analysis which accounted for non-independence of the RR estimates. Goodness-of-fit was tested by comparing observed and predicted lung cancer cases for each level. Inverse-variance weighted meta-analysis allowed derivation of overall β estimates and testing for heterogeneity by factors including sex, age, location, timing, duration, study quality, smoking adjustment, measure of FEV₁ reported, and inverse-variance weight of β.</p> <p>Results</p> <p>Thirty-three publications satisfying the inclusion/exclusion criteria were identified, seven being rejected as not allowing estimation of β. The remaining 26 described 22 distinct studies, from which 32 independent β estimates were derived. Goodness-of-fit was satisfactory, and exp(β), the RR increase per one unit FEV₁%P decrease, was estimated as 1.019 (95%CI 1.016-1.021). The estimates were quite consistent (I² =29.6%). Mean age was the only independent source of heterogeneity, exp(β) being higher for age <50 years (1.024, 1.020-1.028).</p> <p>Conclusions</p> <p>Although the source papers present results in various ways, complicating meta-analysis, they are very consistent. A decrease in FEV₁%P of 10% is associated with a 20% (95%CI 17%-23%) increase in lung cancer risk.</p

Complex multifault rupture during the 2016 Mw 7.8 Kaikōura earthquake, New Zealand

On 14 November 2016, northeastern South Island of New Zealand was struck by a major moment magnitude (Mw) 7.8 earthquake. Field observations, in conjunction with interferometric synthetic aperture radar, Global Positioning System, and seismology data, reveal this to be one of the most complex earthquakes ever recorded. The rupture propagated northward for more than 170 kilometers along both mapped and unmapped faults before continuing offshore at the island’s northeastern extent. Geodetic and field observations reveal surface ruptures along at least 12 major faults, including possible slip along the southern Hikurangi subduction interface; extensive uplift along much of the coastline; and widespread anelastic deformation, including the ~8-meter uplift of a fault-bounded block. This complex earthquake defies many conventional assumptions about the degree to which earthquake ruptures are controlled by fault segmentation and should motivate reevaluation of these issues in seismic hazard models