Bhagyam Full Field Polymer Flood: Implementation and Initial Production Response

Bhagyam is an onshore field in the Barmer basin, located in the state of Rajasthan in Western India. Fatehgarh Formation is the main producing unit, comprising of multi-storied fluvial sandstones. Reservoir quality is excellent with permeability in the range of 1 to 10 Darcy and porosity in the range of 25-30%. The crude is moderately viscous (15 – 500 cP) having a large variation with depth (15 cP – 50 cP from around 270 m TVDSS to 400 m TVDSS and then rising steeply to 500 cp at the OWC of 448m TVDSS). Lab studies on Bhagyam cores show that the reservoir is primarily oil wet in nature. Bhagyam Field was developed initially with edge water injection and with subsequent infill campaigns, prior to polymer flood development plan implementation, the Field was operating with 162 wells. Simple mobility ratio and fractional flow considerations indicate that improving the mobility ratio (water flood end-point mobility ratio is 30-100) in Bhagyam would substantially improve the sweep efficiency. Early EOR screening studies recommended chemical EOR (polymer and ASP flood) as the most suitable method for maximizing oil recovery. The lab studies further demonstrated good recovery potential for Polymer flood. Bhagyam's first Polymer flood field application started with testing in one injector which was later expanded to 8 wells. Extended polymer injection in these wells continued for four years. Observing a very encouraging field response, field scale polymer expansion plan was designed which included drilling of 28 new infill wells (17 P+ 11 I) and 24 producer-to-injector conversions. Modular skid-based polymer preparation units were installed to meet the injection requirements of the expansion plan. Infill producers were brought online in 2018 as per the plan but polymer injection was delayed due to various external factors. The production rate, however, was sustained without significant decline, aided by continuous polymer injection in initial 8 injectors, continuing water flood and good reservoir management practices. First polymer injection in field scale expansion started in Oct’20 and was quickly ramped up to the planned 80000 BPD in 4 months, supported by analyses of surveillance data, indicating very encouraging initial production response. Laboratory quality check program was designed to check quality of polymer during preparation and to ensure viscosity integrity till the well head. The paper discusses modular polymer preparation unit set-up and the additional installations designed to reduce pipeline vibrations during pumping of polymers., Experience gained while bringing online the polymer injection wells and the lab quality checks employed to ensure good polymer quality during preparation and pumping have also been discussed. The paper also discusses reservoir surveillance program adopted at the start of polymer injection like spinner survey, Pressure fall-off surveys and the stimulation activities that worked in improving the injectivity of polymer injectors. The paper further outlines the observations from the production response and the surveillance data collected to ensure good polymer flow in this multi-darcy reservoir.

Use of Machine Learning for Long Term Planning and Cost Minimization in Healthcare Management

The Healthcare system of a country is a crucial infrastructure that requires long-term capacity planning. The covid 19 outbreak pointed to the necessity of adequate hospital capacity, especially for developing countries like Bangladesh. The existing infrastructure planning of these countries emphasizes short-term goals and lacks vision planning for a long time horizon. It is in the country’s best interest to make long-term capacity expansion plans, a strategy the developed countries banked to provide adequate healthcare facilities to their residents. However, no single solution is appropriate for a different region. Hence, it is required to comprehensively study the situation and constraints of the specific region before providing expensive capacity expansion plans. This work focuses on applying a deep Reinforcement Learning based long-term hospital bed capacity expansion plan. We utilize the RNN-LSTM based population forecast, deep Reinforcement Learning (RL) based policy-making, and state-of-the-art Artificial Intelligence techniques to provide a solution. We perform a case study for the Abhaynagar Upazila of Jessore, one of the largest cities in the southwest part of Bangladesh, to analyze the benefits of such an approach compared to existing myopic policies. The experiment results show that the deep RL-based policy significantly minimizes cost over a 30-year expansion plan.

Post Adaptability of Graduates – A Case Study of Business English Majors from H University

In recent years, the number of graduates in employment has increased significantly because of a boom in the number of graduates along with the advancement of the Enrollment Expansion Plan of Colleges and Universities in China. The issues about career selection and graduate employment have been enthusiastically discussed in academic circles as these issues are constantly emphasized by all walks of life. However, academic researchers often neglect matters pertaining graduates when they are already holding positions. This study believes that being employed is not the end point, but a new start, which means that matters pertaining graduates after being employed should also be cared about. This study specifically focuses on the post adaptability of graduates after being employed. In this study, through questionnaires, a number of employed Business English majors from the graduating class of 2011 to 2016 at H university in Shaanxi Province were selected. After that, using the variables from The Fitness Subscale of Adolescent Mental Health Quality Questionnaire, the participants’ post adaptability was studied.

Tesco: Entry and Expansion Strategy in India

The management was reviewing Tesco’s entry into India and its joint venture Trent Hypermarket Private Limited’s operations. After withdrawal from Thailand and Malaysia, India remained one of the most important retail destinations for Tesco. The management was pondering over the expansion of operations in India. The local leadership was entrusted with developing a Roadmap-2025 with an inclusive store expansion plan to build profitability by delivering high customer value.

Welfare-maximizing transmission capacity expansion under uncertainty

We apply the JuDGE optimization package to a multistage stochastic leader–follower model that determines a transmission capacity expansion plan to maximize expected social welfare of consumers and producers who act as Cournot oligopolists in each time period. The problem is formulated as a large-scale mixed integer programme and applied to a 5-bus instance over scenario trees of varying size. The computational effort required by JuDGE is compared with solving the deterministic equivalent mixed integer programme using a state-of-the-art integer programming package. This article is part of the theme issue ‘The mathematics of energy systems’.

Probabilistic power transmission system reliability evaluation

Modern power systems are prudently designed and operated to their brim as allowed by policies and procedures. Many of these utilities have advanced transmission systems built over half a century. With considerable aging transmission asset, their up keep and renewal is very expensive. Probabilistic planning, though computationally cumbersome, is an approach that objectively compares economic risk from aging assets versus cost of upgrades. With a demand for such a generic tool amongst utilities, this thesis presents a probabilistic approach for transmission system expansion planning. The proposed method estimates potential economic losses from aging transmission system assets considering N-1 contingencies where N-1 contingencies represent operation of the transmission system after one element is removed due to fault. Thereafter, the thesis proposes a formulation that computes the best transmission system reinforcement plan to eliminate economic losses from all possible N-1 contingencies. Finally, tests on a sample 7-bus system and IEEE 118-bus system where potential economic losses from N-1 contingencies is compared with transmission system optimal expansion plan are presented. Test results reveal that in certain cases, there is economic merit to upgrade the system and benefit with from a robust transmission system. A 304-bus North American system was also tested and is reported.