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Tight gas reservoirs are mainly developed by multistage hydraulic fracturing horizontal wells (MSHFHWs). A type well provides average production profiles based on real well data and can be constructed from multiple wells to investigate the behavior of the reservoir. For unconventional reservoirs, type wells are the key to reserve calculations and medium- and long-term field development planning. Both geological and completion parameters are key factors affecting single well performance of MSHFHWs. Based on the drilling, hydraulic fracturing, and production data for over 1,800 MSHFHWs in the Montney tight gas reservoir in the Groundbirch region of the Western Canada Sedimentary Basin (WCSB), the main hydraulic fracturing factors affecting the production performance of MSHFHWs were investigated. A rate transient analysis- (RTA-) assisted workflow for type well construction is proposed based on existing production data and considering the geological and engineering factors. Based on the field data, the main hydraulic fracturing factors that affect the production performance of the MSHFHWs in Montney are lateral length, proppant tonnage, and the number of stages. Base type wells are predicted from the P50 wells, which are selected from the wells with normalized lateral length and the same fracturing technique and proppant tonnage. The base type well represents the well performance for a specific drilling and completion background. RTA was introduced to scale up the base type well to predict the type well of new completion design. The new workflow predicts both the base type well with a specific drilling and completion background and the upgraded type well, which uses new completion design. It is highly meaningful and provides a valuable reference to practical studies involving type well prediction in unconventional gas reservoirs. [ABSTRACT FROM AUTHOR]

With the continuous improvement of shale oil and gas recovery technologies and achievements, a large amount of geological information and data have been accumulated for the description of shale reservoirs, and it has become possible to use machine learning methods for "sweet spots" prediction in shale oil and gas areas. Taking the Duvernay shale oil and gas field in Canada as an example, this paper attempts to build recoverable shale oil and gas reserve prediction models using machine learning methods and geological and development big data, to predict the distribution of recoverable shale oil and gas reserves and provide a basis for well location deployment and engineering modifications. The research results of the machine learning model in this study are as follows: ① Three machine learning methods were applied to build a prediction model and random forest showed the best performance. The R2 values of the built recoverable shale oil and gas reserves prediction models are 0.7894 and 0.8210, respectively, with an accuracy that meets the requirements of production applications; ② The geological main controlling factors for recoverable shale oil and gas reserves in this area are organic matter maturity and total organic carbon (TOC), followed by porosity and effective thickness; the main controlling factor for engineering modifications is the total proppant volume, followed by total stages and horizontal lateral length; ③ The abundance of recoverable shale oil and gas reserves in the central part of the study area is predicted to be relatively high, which makes it a favorable area for future well location deployment. [ABSTRACT FROM AUTHOR]

As negotiations for the post-2020 agreement on climate change are underway and expected to be concluded by the end of 2015, the call for ensuring accountability with respect to the implementation of the agreement is attracting increased attention. Hence, one need to have a clear understanding of the meaning of the term "accountability", particularly as it is used in relation to climate change. Accountability, a term used frequently in politics, is rather newin international law. This paper examines the history of achieving accountability in climate change negotiations, and examines that history under three headings, namely, (1) accountability for historical emissions of developed countries, (2) accountability under the Convention and (3) accountability under the Kyoto Protocol. Through a reflection on past accountability practices, this paper intends to establish that two different modes for achieving accountability have emerged: (1) international legal accountability, and (2) international political accountability. These may well provide useful guides to those involved in crafting the post-2020 agreement. As past practice in climate negotiation has shown, achieving accountability has been fraught with difficulties due to its implications for sanctions or political pressures on a sovereign State. These same concerns would persist in the discussion of the accountability regime for the post-2020 agreement. [ABSTRACT FROM AUTHOR]

Duvernay shale is a world class shale deposit with a total resource of 440 billion barrels oil equivalent in the Western Canada Sedimentary Basin (WCSB). The volatile oil recovery factors achieved from primary production are much lower than those from the gas-condensate window, typically 5–10% of original oil in place (OOIP). The previous study has indicated that huff-n-puff gas injection is one of the most promising enhanced oil recovery (EOR) methods in shale oil reservoirs. In this paper, we built a comprehensive numerical compositional model in combination with the embedded discrete fracture model (EDFM) method to evaluate geological and engineering controls on gas huff-n-puff in Duvernay shale volatile oil reservoirs. Multiple scenarios of compositional simulations of huff-n-puff gas injection for the proposed twelve parameters have been conducted and effects of reservoir, completion and depletion development parameters on huff-n-puff are evaluated. We concluded that fracture conductivity, natural fracture density, period of primary depletion, and natural fracture permeability are the most sensitive parameters for incremental oil recovery from gas huff-n-puff. Low fracture conductivity and a short period of primary depletion could significantly increase the gas usage ratio and result in poor economical efficiency of the gas huff-n-puff process. Sensitivity analysis indicates that due to the increase of the matrix-surface area during gas huff-n-puff process, natural fractures associated with hydraulic fractures are the key controlling factors for gas huff-n-puff in Duvernay shale oil reservoirs. The range for the oil recovery increase over the primary recovery for one gas huff-n-puff cycle (nearly 2300 days of production) in Duvernay shale volatile oil reservoir is between 0.23 and 0.87%. Finally, we proposed screening criteria for gas huff-n-puff potential areas in volatile oil reservoirs from Duvernay shale. This study is highly meaningful and can give valuable reference to practical works conducting the huff-n-puff gas injection in both Duvernay and other shale oil reservoirs. [ABSTRACT FROM AUTHOR]

The recent remarkable increase in induced seismicity in Western Canada has been largely attributed to hydraulic fracturing in unconventional reservoirs. The nucleation of large magnitude events has been demonstrated to be closely linked to site-specific geological and operational factors. A mitigation strategy of fracturing-induced seismicity concerning both factors has not been well investigated. In this paper, a comprehensive investigation of risk mitigations from induced seismicity is conducted based on the formation overpressure, distance to Precambrian basement, proximity to faults, fracturing job size and safe hydraulic fracture-fault distance. It is found that the middle-south region near Crooked Lake is an optimal region for fracturing operations with low formation pressure, a great distance to the basement and relatively fewer pre-existing faults. A field case study suggests that fracturing operations of three new horizontal wells are successful with low magnitude induced events and with high production performance, demonstrating the applicability of a comprehensive approach of seismicity risk mitigations. Such an approach can be applied to other field cases to mitigate the potential fracturing-induced seismicity in unconventional reservoirs. [ABSTRACT FROM AUTHOR]

The production of a single gas well is influenced by many geological and completion factors. The aim of this paper is to build a production prediction model based on machine learning technique and identify the most important factor for production. Firstly, around 159 horizontal wells were collected, targeting the Duvernay Formation with detailed geological and completion records. Secondly, the key factors were selected using grey relation analysis and Pearson correlation. Then, three statistical models were built through multiple linear regression (MLR), support vector regression (SVR), gaussian process regression (GPR). The model inputs include fluid volume, proppant amount, cluster counts, stage counts, total horizontal lateral length, gas saturation, total organic carbon content, condensate-gas ratio. The model performance was assessed by root mean squared errors (RMSE) and R-squared value. Finally, sensitivity analysis was applied based on best performance model. The analysis shows following conclusions: (1) GPR model shows the best performance with the highest R-squared value and the lowest RMSE. In the testing set, the model shows a R-squared of 0.8 with a RMSE of 280.54 × 104 m3 in the prediction of cumulative gas production within 1st 6 producing months and gives a R-squared of 0.83 with a RMSE of 1884.3 t in the prediction of cumulative oil production within 1st 6 producing months (2) Sensitivity analysis based on GPR model indicates that condensate-gas ratio, fluid volume, and total organic carbon content are the most important features to cumulative oil production within 1st 6 producing months. Fluid volume, Stages, and total organic carbon content are the most significant factors to cumulative gas production within 1st 6 producing months. The analysis progress and results developed in this study will assist companies to build prediction models and figure out which factors control well performance. [ABSTRACT FROM AUTHOR]

Organocatalyzed asymmetric Friedel–Craft reactions have enabled the rapid construction of chiral molecules with highly enantioselectivity enriching the toolbox of chemists for producing complex substances. Here, we report N-heterocyclic carbene-catalyzed asymmetric indole Friedel–Crafts alkylation-annulation with α,β-unsaturated acyl azolium as the key intermediate, affording a large variety of indole-fused polycyclic alkaloids with excellent diastereo- and enantioselectivities. The reaction mechanism is also investigated, and the reaction products can be easily converted to highly functionalized indole frameworks with different core structures. Indole-fused polycyclic alkaloids are present in numerous bioactive natural products. Here an enantioselective N-heterocyclic carbene-catalysed Friedel–Crafts alkylation/annulation cascade using acyl azolium salts as the electrophile provides access to these products with high stereoselectivity. [ABSTRACT FROM AUTHOR]