Water management can significantly add to the cost and environmental footprint of oil production and innovations in water management can provide significant economic and environmental gains. New treatment technologies make recycling of water for hydraulic fracturing possible. Methods for recycling fracking water include anaerobic and aerobic biologic treatment; clarification; filtration; electrocoagulation; blending (directly diluting wastewater with freshwater); and evaporation. Generally, anaerobic treatments on wastewater are implemented on concentrated wastewater. Anaerobic sludge contains a variety of microorganisms that cooperate to convert organic material to biogas via hydrolysis and acidification.
Bagheri, Mohammadreza (Research Centre for Fluid and Complex Systems, Coventry University) | Shariatipour, Seyed M. (Research Centre for Fluid and Complex Systems, Coventry University) | Ganjian, Eshmaiel (School of Energy, Construction and Environment, Built & Natural Environment Research Centre, Coventry University)
The fluid pressure, the stress due to the column of the cement in the annulus of oil and gas wells, and the radial pressure exerted on the cement sheath from the surrounding geological layers all affect the integrity of the cement sheath. This paper studies the impact of CO2-bearing fluids, coupled with the geomechanical alterations within the cement matrix on its integrity. These geochemical and geomechanical alterations within the cement matrix have been coupled to determine the cement lifespan. Two main scenarios including radial cracking and radial compaction, were assumed in order to investigate the behaviour of the cement matrix exposed to CO2-bearing fluids over long periods. If the radial pressure from the surrounding rocks on the cement matrix overcomes the strength of the degraded layers within the cement matrix, cement failure can be postponed, while on the other hand, high vertical stress on the cement matrix in the absence of a proper radial pressure can lead to a reduction in the cement lifespan. The radial cracking process generates local areas of high permeability around the outer face of the cement sheath. Our simulation results show at the shallower depths the cement matrices resist CO2-bearing fluids more and this delays exponentially the travel time of CO2-bearing fluids towards the Earth's surface. This is based on the evolution of CO2 gas from the aqueous phase due to the reduction in the fluid pressure at shallower depths, and consumption of CO2 in the reactions which occur at the deeper locations.
Recent studies have indicated that Huff-n-Puff (HNP) gas injection has the potential to recover an additional 30-70% oil from multi-fractured horizontal wells in shale reservoirs. Nonetheless, this technique is very sensitive to production constraints and is impacted by uncertainty related to measurement quality (particularly frequency and resolution), and lack of constraining data. In this paper, a Bayesian workflow is provided to optimize the HNP process under uncertainty using a Duvernay shale well as an example.
Compositional simulations are conducted which incorporate a tuned PVT model and a set of measured cyclic injection/compaction pressure-sensitive permeability data. Markov chain Monte Carlo (McMC) is used to estimate the posterior distributions of the model uncertain variables by matching the primary production data. The McMC process is accelerated by employing an accurate proxy model (kriging) which is updated using a highly adaptive sampling algorithm. Gaussian Processes are then used to optimize the HNP control variables by maximizing the lower confidence interval (μ-σ) of cumulative oil production (after 10 years) across a fixed ensemble of uncertain variables sampled from posterior distributions.
The uncertain variable space includes several parameters representing reservoir and fracture properties. The posterior distributions for some parameters, such as primary fracture permeability and effective half-length, are narrower, while wider distributions are obtained for other parameters. The results indicate that the impact of uncertain variables on HNP performance is nonlinear. Some uncertain variables (such as molecular diffusion) that do not show strong sensitivity during the primary production strongly impact gas injection HNP performance. The results of optimization under uncertainty confirm that the lower confidence interval of cumulative oil production can be maximized by an injection time of around 1.5 months, a production time of around 2.5 months, and very short soaking times. In addition, a maximum injection rate and a flowing bottomhole pressure around the bubble point are required to ensure maximum incremental recovery. Analysis of the objective function surface highlights some other sets of production constraints with competitive results. Finally, the optimal set of production constraints, in combination with an ensemble of uncertain variables, results in a median HNP cumulative oil production that is 30% greater than that for primary production.
The application of a Bayesian framework for optimizing the HNP performance in a real shale reservoir is introduced for the first time. This work provides practical guidelines for the efficient application of advanced machine learning techniques for optimization under uncertainty, resulting in better decision making.
Since decades, steam-assisted oil recovery processes have been successfully deployed in heavy oil reservoirs to extract bitumen/heavy oil. Current resource allocation practices mostly involve reservoir model-based open loop optimization at the planning stage and its periodic recurrence. However, such decades-old strategies need a complete overhaul as they ignore dynamic changes in reservoir conditions and surface facilities, ultimately rendering heavy oil production economically unsustainable in the low-oil-price environment. Since steam supply costs account for more than 50% of total operating costs, a data-driven strategy that transforms the data available from various sensors into meaningful steam allocation decisions requires further attention.
In this research, we propose a purely data-driven algorithm that maximizes the economic objective function by allocating an optimal amount of steam to different well pads. The method primarily constitutes two components: forecasting and nonlinear optimization. A dynamic model is used to relate different variables in historical field data that were measured at regular time intervals and can be used to compute economic performance indicators (EPI). The variables in the model are cumulative in nature since they can represent the temporal changes in reservoir conditions. Accurate prediction of EPI is ensured by retraining regression model using the latest available data. Then, predicted EPI is optimized using a nonlinear optimization algorithm subject to amplitude and rate saturation constraints on decision variables i.e., amount of steam allocated to each well pad.
Proposed steam allocation strategy is tested on 2 well pads (each containing 10 wells) of an oil sands reservoir located near Fort McMurray in Alberta, Canada. After exploratory analysis of production history, an output error (OE) model is built between logarithmically transformed cumulative steam injection and cumulative oil production for each well pad. Commonly used net-present-value (NPV) is considered as EPI to be maximized. Optimization of the objective function is subject to distinct operating conditions and realistic constraints. By comparing results with field production history, it can be observed that optimum steam injection profiles for both well pads are significantly different than that of a field. In fact, the proposed algorithm provides smooth and consistent steam injection rates, unlike field injection history. Also, the lower steam-oil ratio is achieved for both well pads, ultimately translating into ~19 % higher NPV when compared with field data.
Inspired from state-of-the-art control techniques, proposed steam allocation algorithm provides a generic data-driven framework that can consider any number of well pads, EPIs, and amount of past data. It is computationally inexpensive as no numerical simulations are required. Overall, it can potentially reduce the energy required to extract heavy oil and increase the revenue while inflicting no additional capital cost and reducing greenhouse gas emissions.
Penghui, Su (PetroChina Research Institute of Petroleum Explorationand and Development) | Zhaohui, Xia (PetroChina Research Institute of Petroleum Explorationand and Development) | Ping, Wang (PetroChina Research Institute of Petroleum Explorationand and Development) | Liangchao, Qu (PetroChina Research Institute of Petroleum Explorationand and Development) | xiangwen, Kong (PetroChina Research Institute of Petroleum Explorationand and Development) | Wenguang, Zhao (PetroChina Research Institute of Petroleum Explorationand and Development)
Interest has spread to potential unconventional shale reservoirs in the last decades, and they have become an increasingly important source of hydrocarbon. Importantly, pore structure of shale has considerable effects on the storage, seepage and output of the fluids in shale reservoirs so that reliable fractal characteristics are essential. To better understand the evolution characteristics of pore structure for a shale gas condensate reservoir and their influence on liquid hydrocarbon occurrences and reservoir physical properties, we conducted high-pressure mercury intrusion tests (HPMIs), field emission scanning electron microscopies (FESEM), total organic carbon (TOC), Rock-Eval pyrolysis and saturation measurements on samples from the Duvernay formation. Furthermore, the fractal theory is applied to calculate the fractal dimension of the capillary pressure curves, and three fractal dimensions D1, D2 and D3 are obtained. The relationships among the characteristics of the Duvernay shale (TOC, organic matter maturity, fluid saturation), the pore structure parameters (permeability, porosity, median pore size), and the fractal dimensions were investigated.
The results show that the fractal dimension D1 ranges from 2.44 to 2.85, D2 ranges from 2.09 to 2.15 and D3 ranges from 2.35 to 2.48. D2 and D3 have a good positive correlation. The pore system studied mainly consists of organic pores and microfractures, with the percentage of micropores being 50.38%. TOC has a positive relationship with porosity and D3 due to the development of organic pores. D3 has a positive correlation with gas saturation. With increased D3, median pore size shows a decreasing trend and an increase in permeability and porosity, demonstrating that D3 has a large effect on pore size distribution and the heterogeneity of pore size. In general, D3 has a better correlation with petrophysical and petrochemical parameters. Fractal theory can be applied to better understand the pore evolution, pore size distribution and fluid storage capacity of shale reservoirs.
It’s no secret that oil majors are among the biggest corporate emitters of pollution. What may be surprising is that they’re reducing their greenhouse-gas footprints every year, actively participating in a trend that’s swept up most corporate behemoths. The Canadian and Alberta governments and three energy companies said on 11 May that they will spend CAD 70 million (USD 51.14 million) to develop three new clean technology projects, aimed at cutting costs and carbon emissions in the country’s oil sands.
An improved occupational health and safety system comes into effect on 1 June to better protect Alberta workers and ensure they have the same rights as other Canadians. The Alberta Energy Regulator has issued two draft directives that will require upstream oil and gas operators to reduce methane emissions from upstream oil and gas sites by 45% from 2014 levels by 2025. On 16 June 2017, the Alberta Oil Sands Advisory Group released its report Recommendations on Implementation of the Oil Sands Emissions Limit Established by the Alberta Climate Leadership Plan.
Royal Dutch Shell is changing its tune on carbon, saying it will tie executive pay to shorter-term reductions in emissions. A dire government report on the far-reaching impact of climate change could increase pressure on the energy industry to curb greenhouse gas emissions and political leaders to act more decisively to reduce the use of fossil fuels, analysts said. Climate change involves a combination of factors that make it hard for people to get motivated. The city of Baltimore filed a lawsuit on 20 July against 26 oil and gas companies and entities, including BP, Chevron, and ExxonMobil, for knowingly contributing to what the city called the catastrophic consequences of climate change. A California federal court dismissed climate change lawsuits against five oil companies by the cities of San Francisco and Oakland, saying the complaints required foreign and domestic policy decisions that were outside the purview of courts, Chevron said on 25 June.
State health officials say they will review whether exemptions for the fossil fuels industry violates the Clean Air Act. Colorado lawmakers approved a bill overhauling regulations governing the state’s robust oil and gas industry to prioritize public health and safety, over opposition by Republicans and industry groups. Oregon has permanently banned offshore drilling in the midst of a federal push to open 90% of federal waters to oil exploration. A federal judge in Alaska has ruled an executive order by President Donald Trump allowing offshore oil drilling of tens of millions of acres in the Arctic Ocean is "unlawful and invalid." The US Environmental Protection Agency plans to issue a rule regulating methane emissions later this year, administrator Andrew Wheeler said.
This paper presents a state-of-the-art review of scale-inhibitor-analysis techniques and describes how these techniques can be used to provide cost-effective scale management. Calcium sulfate (CaSO4) in the form of gypsum and anhydrite is one of the more prevalent evaporite minerals typically found in the carbonate rocks of the western Canadian sedimentary basin (WCSB).