Dataset Information

Induced seismicity closed-form traffic light system for actuarial decision-making during deep fluid injections.

ABSTRACT: The rise in the frequency of anthropogenic earthquakes due to deep fluid injections is posing serious economic, societal, and legal challenges to many geo-energy and waste-disposal projects. Existing tools to assess such problems are still inherently heuristic and mostly based on expert elicitation (so-called clinical judgment). We propose, as a complementary approach, an adaptive traffic light system (ATLS) that is function of a statistical model of induced seismicity. It offers an actuarial judgement of the risk, which is based on a mapping between earthquake magnitude and risk. Using data from six underground reservoir stimulation experiments, mostly from Enhanced Geothermal Systems, we illustrate how such a data-driven adaptive forecasting system could guarantee a risk-based safety target. The proposed model, which includes a linear relationship between seismicity rate and flow rate, as well as a normal diffusion process for post-injection, is first confirmed to be representative of the data. Being integrable, the model yields a closed-form ATLS solution that is both transparent and robust. Although simulations verify that the safety target is consistently ensured when the ATLS is applied, the model from which simulations are generated is validated on a limited dataset, hence still requiring further tests in additional fluid injection environments.

SUBMITTER: Mignan A

PROVIDER: S-EPMC5648767 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Induced seismicity closed-form traffic light system for actuarial decision-making during deep fluid injections.

Mignan A A Broccardo M M Wiemer S S Giardini D D

Scientific reports 20171019 1

The rise in the frequency of anthropogenic earthquakes due to deep fluid injections is posing serious economic, societal, and legal challenges to many geo-energy and waste-disposal projects. Existing tools to assess such problems are still inherently heuristic and mostly based on expert elicitation (so-called clinical judgment). We propose, as a complementary approach, an adaptive traffic light system (ATLS) that is function of a statistical model of induced seismicity. It offers an actuarial ju ...[more]

PMID: 29051528

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Project description:OBJECTIVES:We sought to evaluate the efficacy, efficiency, and physiologic consequences of automated, endpoint-directed resuscitation systems and compare them to formula-based bolus resuscitation. DESIGN:Experimental human hemorrhage and resuscitation. SETTING:Clinical research laboratory. SUBJECTS:Healthy volunteers. INTERVENTIONS:Subjects (n = 7) were subjected to hemorrhage and underwent a randomized fluid resuscitation scheme on separate visits 1) formula-based bolus resuscitation; 2) semiautonomous (decision assist) fluid administration; and 3) fully autonomous (closed loop) resuscitation. Hemodynamic variables, volume shifts, fluid balance, and cardiac function were monitored during hemorrhage and resuscitation. Treatment modalities were compared based on resuscitation efficacy and efficiency. MEASUREMENTS AND MAIN RESULTS:All approaches achieved target blood pressure by 60 minutes. Following hemorrhage, the total amount of infused fluid (bolus resuscitation: 30?mL/kg, decision assist: 5.6?±?3?mL/kg, closed loop: 4.2?±?2?mL/kg; p < 0.001), plasma volume, extravascular volume (bolus resuscitation: 17?±?4?mL/kg, decision assist: 3?±?1?mL/kg, closed loop: -0.3?±?0.3?mL/kg; p < 0.001), body weight, and urinary output remained stable under decision assist and closed loop and were significantly increased under bolus resuscitation. Mean arterial pressure initially decreased further under bolus resuscitation (-10?mm Hg; p < 0.001) and was lower under bolus resuscitation than closed loop at 20 minutes (bolus resuscitation: 57?±?2?mm Hg, closed loop: 69?±?4?mm Hg; p = 0.036). Colloid osmotic pressure (bolus resuscitation: 19.3?±?2?mm Hg, decision assist, closed loop: 24?±?0.4?mm Hg; p < 0.05) and hemoglobin concentration were significantly decreased after bolus fluid administration. CONCLUSIONS:We define efficacy of decision-assist and closed-loop resuscitation in human hemorrhage. In comparison with formula-based bolus resuscitation, both semiautonomous and autonomous approaches were more efficient in goal-directed resuscitation of hemorrhage. They provide favorable conditions for the avoidance of over-resuscitation and its adverse clinical sequelae. Decision-assist and closed-loop resuscitation algorithms are promising technological solutions for constrained environments and areas of limited resources.

Project description:BackgroundSome patients involved in a road traffic collision (RTC) are physically entrapped and extrication is required to provide critical interventions. This can be performed either in an expedited way, or in a more controlled manner. In this study we aimed to derive a data-driven extrication algorithm intended to be used as a decision-support tool by on scene emergency service providers to decide on the optimal method of patient extrication from the vehicle.MethodsA retrospective observational study was performed of all trauma patients trapped after an RTC who were attended by a Helicopter Emergency Medical Service (HEMS) in the United Kingdom between March 2013 and December 2021. Variables were identified that were associated with the need for HEMS interventions (as a surrogate for the need for expedited extrication), based on which a practical extrication algorithm was devised.ResultsDuring the study period 12,931 patients were attended, of which 920 were physically trapped. Patients who scored an "A" on the AVPU score (n = 531) rarely required HEMS interventions (3%). Those who did were characterised by a shorter than average (29 vs. 37 min) 999/112 emergency call to HEMS on-scene arrival interval. A third of all patients responding to voice required HEMS interventions. Absence of a patent airway (OR 6.98 [1.74-28.03] p < .001) and the absence of palpable radial pulses (OR 9.99 [2.48-40.18] p < .001) were independently associated with the need for (one or more) HEMS interventions in this group. Patients only responding to pain and unresponsive patients almost invariably needed HEMS interventions post extrication (90% and 86% respectively). Based on these findings, a practical and easy to remember algorithm "APEX" was derived.ConclusionA simple, data-driven algorithm, remembered by the acronym "APEX", may help emergency service providers on scene to determine the preferred method of extrication for patients who are trapped after a road traffic collision. This has the potential to facilitate earlier recognition of a 'sick' critical patient trapped in an RTC, decrease entrapment and extrication time, and may contribute to an improved outcome for these patients.

Dataset Information

Induced seismicity closed-form traffic light system for actuarial decision-making during deep fluid injections.

Publications

Induced seismicity closed-form traffic light system for actuarial decision-making during deep fluid injections.

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