Grover, Kavish (Cairn Oil & Gas, Vedanta Limited) | Kolay, Jayabrata (Cairn Oil & Gas, Vedanta Limited) | Kumar, Ritesh (Cairn Oil & Gas, Vedanta Limited) | Ghosh, Priyam (Cairn Oil & Gas, Vedanta Limited) | Shekhar, Sunit (Cairn Oil & Gas, Vedanta Limited) | Agrawal, Nitesh (Cairn Oil & Gas, Vedanta Limited) | Das, Joyjit (Cairn Oil & Gas, Vedanta Limited)
For any typical water flood or polymer flood management, maintaining optimum Voidage Replacement Ratio (VRR) is most crucial for optimizing reservoir performance. In a typical patternflood, a single injector supports many nearby producers, determining its contribution to particular producer is subjective and has inherent uncertainties. To avoid these uncertainties in allocation factor, a novel approach using simulation model based voidage compensation on pattern by pattern basis has been proposed in this paper.
History matched simulation model, which has been sectored into 5-spot producer centric patterns, forms the basis of this study. Voidage replacements are analyzed on these producer centric 5-spot patterns. Sectoral voidage created is determined using change in hydrocarbon pore volume (HCPV), water pore volume (WPV) and production from the sector. Sectoral Voidage Compensation Ratio (or Pseudo VRR) thus calculated is representative of the net change due to injection and production. The advantage is that it does not require any numerical allocation factor, rather is based on fluid movements within a pattern as predicted by the simulation model. This method thus provides a new approach to analyze pattern performance.
Along with VRR, pattern wise recovery and interwell channeling/cycling are the key parameters for any water flood performance analysis. A workflow has been proposed to rank the patterns based on these parameters and categorizing them into problem buckets. Actions corresponding to each bucket have been proposed. This forms the basis of strategizing improvements in well-by-well and pattern-by-pattern performance for optimizing field performance.
Agrawal, Nitesh (Cairn Oil & Gas, Vedanta Limited) | Chapman, Tom (Cairn Oil & Gas, Vedanta Limited) | Baid, Rahul (Cairn Oil & Gas, Vedanta Limited) | Singh, Ritesh Kumar (Cairn Oil & Gas, Vedanta Limited) | Shrivastava, Sahil (Cairn Oil & Gas, Vedanta Limited) | Kushwaha, Malay Kumar (Cairn Oil & Gas, Vedanta Limited) | Kolay, Jayabrata (Cairn Oil & Gas, Vedanta Limited) | Ghosh, Priyam (Cairn Oil & Gas, Vedanta Limited) | Das, Joyjit (Cairn Oil & Gas, Vedanta Limited) | Khare, Sameer (Cairn Oil & Gas, Vedanta Limited) | Kumar, Piyush (Cairn Oil & Gas, Vedanta Limited) | Aggarwal, Shubham (Cairn Oil & Gas, Vedanta Limited)
The objective of this paper is to present a suite of diagnostic methods and tools which have been developed to analyse and understand production performance degredation in wells lifted by ESPs in the Mangala field in Rajasthan, India. The Mangala field is one of the world’s largest full field polymer floods, currently injecting some 450kbbl/day of polymerized water, and a significant proportion of production is lifted with ESPs. With polymer breaking through to the producers, productivity and ESP performance in many wells have changed dramatically. We have observed rapidly reducing well productivity indexes (PI), changes to the pumps head/rate curve, increased inlet gas volume fraction (GVF) and reduction in the cooling efficiency of ESP motors from wellbore fluids. The main drivers for the work were to understand whether reduced well rates were a result of reduced PI or a degredation in the ESP pump curve, and whether these are purely down to polymer or combined with other factors, for example reduced reservoir pressure, increasing inlet gas, scale buildup, mechanical wear or pump recirculation.
The methodology adopted for diagnosis was broken in 5 parts – 1) Real time ESP parameter alarm system, 2) Time lapse analysis of production tubing pressure drop, 3) Time lapse analysis of pump head de-rating factor, 4) Time lapse analysis of pump and VFD horse power 5) Dead head and multi choke test data. With this workflow we were able to break down our understanding of production loss into its constituent components, namely well productivitiy, pump head/rate loss or additional tubing pressure drop. It was also possible to further make a data driven asseesment as to the most likely mechanisms leading to ESP head loss (and therefore rate loss), to be further broken own into whether this was due to polymer plugging, mechanical wear, gas volume fraction (GVF) de-rating, partial broken shaft/locked diffusers or holes/recirculation. In some cases a specific mechanism was compounded with an associated impact. For example, in ESPs equipped with an inlet screen, heavy polymer deposition over the screen was resulting in large pressure drops across the screen leading to lower head, but this also resulted in higher GVFs into first few stages of the pump, even though the GVF outside the pump were low, leading to further head loss from gas de-rating of the head curve. With knowledge of the magnitude of production losses from each of the underlying mechanisms, targeted remediation could then be planned.
The well and pump modelling adopted in the workflow utilise standard industry calculations, but the combination of these into highly integrated visual displays combined with time lapse analysis of operating performance, provide a unique solution not seen in commercial software we have screened.
The paper also provides various real field examples of ESP performance deterioration, showing the impact of polymer deposition leading to increased pump hydraulic friction losses, pump mechanical failure and high motor winding temperature. Diagnoses based on the presented workflow have in many cases been verified by inspection reports on failed ESPs. Diagnosis on ESPs that have not failed cannot be definitive, though the results of remediation (eg pump flush) can help to firm up the probable cause.
Sharma, K Kaladhar (Cairn India Ltd) | Mishra, Sudhakar (Cairn India Ltd) | Kumar, Pankaj (Cairn India Ltd) | Pandey, Amitabh (Cairn India Ltd) | Jain, Shakti (Cairn India Ltd) | Ghosh, Priyam (Cairn India Ltd) | Mishra, Lokranjan (Cairn India Ltd) | Koduru, Nitish (Cairn India Ltd) | Agrawal, Nitesh (Cairn India Ltd) | Kushwaha, Malay Kumar (Cairn India Ltd)
The Bhagyam Field development is part of the Mangala- Bhagyam -Aishwariya (MBA) development in the Barmer Basin, Rajasthan, India. The Bhagyam field is a shallow field with ~12B dip, containing good quality fluvial sand(s), medium gravity crude with a viscosity gradient (vertically) in the oil column and low water salinity (~5000 ppm). The field is currently being developed using down-dip water injection. The effectiveness of the waterflood will be limited by the adverse mobility ratio and reservoir heterogeneities. A polymer injectivity test was conducted in two wells with two main objectives: (1) to establish injectivity within the designed surface pressure, and (2) establish the ability to prepare polymer solutions of the desired viscosity using produced water for re-injection (PWRI).
Operationally, the test was conducted using a skid mounted unit with regular monitoring facilities in place. Surveillance activities included frequent spinner surveys, bottom-hole pressure measurements, fall-off tests and offset production well tests. Rigorous monitoring of injection water quality, polymer solution quality was carried out. An inline viscometer was used for continuous polymer viscosity monitoring. This was supplemented by periodic sample viscosity measurements using special samplers with chemical stabilizers. The test was conducted in two wells and important lessons have been learnt which would be incorporated during full-field implementation of a polymer flood in Bhagyam.
The injectivity test establishes that polymer injection is viable in Bhagyam Fatehgarh reservoirs. A history matching exercise was carried out using a sector model extracted from our full-field simulation model. The effect of production and injection in offset wells was captured in the sector model. Local grid refinement enabled us to adequately capture polymer rheology. The modelled rheology was found to be in close agreement with laboratory data. The production history of the wells in the sector and vertical injection profile of the injector well was incorporated. We obtained a good history match of the injection bottom-hole pressures.
This paper presents details of the polymer injectivity tests including bottom-hole pressure measurements, fall-off tests and production logging which were conducted during the tests. As PWRI was utilized for preparing polymer solution, the effect of additives to the polymer solution viscosity was also analyzed. The test included use of not so commonly used equipment like inline viscometer, special samplers with chemical stabilizers, preparation of high concentration mother solution and injection of heated polymer solution.
Progressive Cavity Pumps (PCPs), if properly sized, can greatly improve a well's deliverability and run-life. As a result, PCP sizing for a large number of wells can be instrumental in a production optimization program. This paper presents a quick look methodology adopted in the Bhagyam field to better understand PCP system performance and to accurately predict pump deliverability under a wide range of downhole conditions for more than a hundred wells. Using nodal analysis, this paper presents the procedure used to select optimum pump size and well fluid rates from well inflow and outflow performance. The paper also presents a correction factor for the effect of viscosity on pump performance and uses the corrected pump performance curves to model the expected liquid rate from a well. The solutions obtained with the analyses have been validated against actual Bhagyam well test data and have proved to be fairly consistent. This procedure has not only been a useful tool for pump selection and performance monitoring but has also made a significant business impact in terms of incremental oil gain.The methodology quickly provides reasonably accurate solutions for pump selection and allows evaluation of real time pump parameters to optimize PCP under varying field conditions.
This paper demonstrates a novel technique of tracking water entry zones, which has been used with a good success rate in Bhagyam field. Bhagyam field is located in the state of Rajasthan, India and is a part of the prolific Barmer Basin. Oil Production from Bhagyam field has shown steep decline as the water cut increased sharply. The reason for the increase in water cut can be largely attributed to adverse mobility ratio and limited volumetric pump capacities which limit drawdown. The excess water not only has reduced oil rates but also increased liquid volumes at the processing terminal. In order to control operating costs and increase oil production, it was of paramount importance for the operator to carry out water shut off jobs as a measure to reduce the undesirable water production.
This paper illustrates firstly a systematic approach on how the water entry zones are identified with the help of dead oil viscosity data and secondly describes a few case histories of water shut off jobs. Mechanical water shut off techniques were used to isolate bottom watered out sands temporarily. Retrievable bridge plugs were installed above the watered out zones during work-overs to increase drawdown on other sands and increase oil recovery. Using this methodology, four water shut off jobs were executed successfully in FY 2014–15 which led to significant reduction in water production and subsequent increase in oil production.
Farooqui, M.Y. (Gujarat State Petroleum Corp.) | Ghosh, Ujjal (Gujarat State Petroleum Corp.) | Ray, Arijit (GSPC) | Gupta, Sourabh Datta (Gujarat State Petroleum Corp) | Sarkar, Debjani (Gujarat State Petroleum Corp) | Ghosh, Priyam (Schlumberger) | Srigiriraju, Ramachandra (Schlumberger) | Sagar, Rajiv (Schlumberger) | Srivastva, Chandramani (Schlumberger) | Bhadra, Sutapa (Schlumberger) | Natarajan, Karthik Kumar (Schlumberger) | Agarwal, Gunja (Schlumberger) | Rao, Dhiresh Govind (Schlumberger) | Carrillat, Alexis