We report the results of the first large-scale international survey of public perception of geoengineering and solar radiation management (SRM). Our sample of 3105 individuals in the United States, Canada and the United Kingdom was recruited by survey firms that administer internet surveys to nationally representative population samples. Measured familiarity was higher than expected, with 8% and 45% of the population correctly defining the terms geoengineering and climate engineering respectively. There was strong support for allowing the study of SRM. Support decreased and uncertainty rose as subjects were asked about their support for using SRM immediately, or to stop a climate emergency. Support for SRM is associated with optimism about scientific research, a valuing of SRM's benefits and a stronger belief that SRM is natural, while opposition is associated with an attitude that nature should not be manipulated in this way. The potential risks of SRM are important drivers of public perception with the most salient being damage to the ozone layer and unknown risks. SRM is a new technology and public opinions are just forming; thus all reported results are sensitive to changes in framing, future information on risks and benefits, and changes to context.

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High-resolution acoustic imaging technology provides operators the ability to extract submillimetric measurements of perforations at any depth into the casing wall. Due to its three-dimensional nature, submillimetric acoustic data permits the extraction of highly accurate area-based measurements at any radial distance into the perforation, with key distances at the inner and outer casing boundary. This novel technology is fluid agnostic and is unaffected by fluid opacity or clarity. The platforms robust 3D measurement capabilities have made it into an ideal means to evaluate casing and perforations in challenging environments such as hydraulically fractured wells. The integration of high-resolution acoustic imaging into numerous operators’ hydraulic fracture and completions evaluation workflows has resulted in a highly insightful aggregate submillimetric perforation dataset. This large dataset has led to the development of a method to virtually unplug perforations by using a well-specific "perforation entry and exit-hole area correlation". The correlation established can only be extracted using acoustic based imaging as it requires submillimetric resolution of both the ID and OD profile of each perforation Using this correlation, the resulting set of post-frac perforation exit-hole measurements improves an operators’ ability to complete a holistic well completion evaluation, even when well conditions cause perforations to be plugged. The outcome is improved operational insight through the ability to directly compare stages with plugged perforations to those without. This approach can be applied at any point in the well's life cycle, which allows operators to revisit assessments and virtually unplug obscured and proppant-filled perforations. The methodology requires a sound baseline knowledge of the performance of the downhole perforating charges. The baseline is commonly obtained through a calibration stage, which is a stage of charges that are shot but left unstimulated to provide the control measurements for the specific charge in the given well conditions. Current industry performance of downhole perforating charges is investigating through the aggregated dataset of calibration charges. To validate this solid-state acoustic technology and demonstrates its high degree of accuracy for entry and exit-hole perforation measurements, machined samples were scanned with this technology, and with a metrology-grade laser scanner for comparison. This paper presents a novel virtual unplugging methodology, enabled by highly accurate and validated entry-hole measurements, as well as other insights garnered from the aggregate analysis of the world's largest calibration perforation datasets.

Many operators have used in the past various methods to analyze and optimize the horizontal well (HW) completions in the Eagle Ford play with varied results. Typically, such methods focus on different parts of this complex problem in relative isolation and as a consequence do not utilize all available data simultaneously. This paper presents a simulation-based method for analyzing the problem in an integrated fashion by modeling the fracturing and Stimulated Reservoir Volume (SRV) creation process, followed by well cleanup and production. Consequently, all available data are used to constrain the history match (HM), resulting in a more reliable tool for optimization. In this work, the authors developed a comprehensive integrated model of a typical Eagle Ford well in the Dimmit County. The HM process showed that injection and production scenarios must be modeled in tandem to get better insights into the flow physics rather than simulating them separately. The best accuracy is obtained when the real sequence of fracturing is modeled. It was found that only a fraction of the created fracture and SRV lengths contribute to production. Whereas fracture half-lengths of ~250 ft were generated during injection, only about ¼ of fracture and ¾ of SRV contributed. Effect of completion efficiency was also investigated. It was shown that the assumption of only 2 perforation clusters per stage is not plausible while assuming some other scenarios offers good HM and prediction very similar to uniform efficiency. Optimization work considered several scenarios. Cases with larger cluster/stage spacing with the same pumped volume are not desirable. However, the use of double the cluster spacing gives slightly higher estimated ultimate recovery in 30 years, and could offer significant completion cost savings. Use of current injection volumes and current well spacing (500 ft) leaves significant reservoir volume undrained, which is a target for well spacing optimization. Pressure (as opposed to stress) dependent permeability functions adequately capture the permeability variation both for injection and production. The work shows how the integrated reservoir/fracturing/geomechanics modeling can be used to optimize completions and EUR for shale wells.