Application of Ultrashort Radius Lateral Drilling Technique in Top Thick Reservoir Exploitation after Long Term Water Flooding

2016 ◽  
Author(s):  
He Liu ◽  
Shouzhi Huang ◽  
Qiang Sun ◽  
Eryang Ming ◽  
Tao Li ◽  
...  
Keyword(s):  
Water Flooding ◽  
Drilling Technique

Doubling its Production in One Year: Reviving a Brown Field in South of Oman

2021 ◽  
Author(s):  
Suria Amalia Suut ◽  
Mahmood Khamis Al Kalbani ◽  
Issa Quseimi ◽  
Abdullah Gahaffi ◽  
Arjen Wielaard ◽  
...  
Keyword(s):  
Data Analysis ◽  
Water Injection ◽  
Data Gathering ◽  
Water Flooding ◽  
Success Story ◽  
Full Field ◽  
One Year ◽  
Clastic Reservoirs ◽  
Low Rate

Abstract This paper summarises a ONE development success story of reviving a mature brownfield in South of Oman, Field β, just within ONE year through collaboration between different disciplines, comprehensive data analysis, optimising and recompletion of existing wells. Field β, comprised of multi-stacked clastic reservoirs, was put on stream in 1980s and peaked in early 1990s. Pilot water injection started in 1993 and full field water flooding continued in 1997. After more than 35 years since start of production, one can say the field was already in the tail end of its life. It had been stabilizing at low rate after 25 years and starting to decline further and at some point was one of the potential candidates to be decommissioned. A new FDP (FDP18) for part of the field was delivered in 2018 with the first well drilled at the end of that year. In 2019, despite drilling further wells on the FDP18, production was declining and was at 2018 rate towards the year end. Intensive data analysis and integrated reservoir reviews per reservoir layers were actively performed and new opportunities and data gathering were identified. FDP18 wells from 2019 onwards were then deepened to also acquire log data over deeper than the target reservoirs. Further synergy between asset and exploration teams also instigated in new discoveries including oil in shallower carbonate reservoirs, which were logged and sampled when drilling the FDP18 wells. Declining production, low oil price and COVID-19 crisis that hit 2020 challenged the team to be more resilient and with ONE development mindset between development and WRFM team, also between asset and exploration team, existing long-term closed in and very low productivity wells were utilised to tap these new opportunities. As a result, the field production has been increased by more than double, highest since 10 years ago, with a potential of triple its production rate, all achieved through optimizing and recompletion of existing wells within 1 year, at a very attractive low UTC.

scholarly journals Microbial diversity and abundance in the Xinjiang Luliang long‐term water‐flooding petroleum reservoir

2015 ◽  
Vol 4 (2) ◽  
pp. 332-342 ◽  
Author(s):  
Peike Gao ◽  
Huimei Tian ◽  
Guoqiang Li ◽  
Hongwen Sun ◽  
Ting Ma
Keyword(s):  
Microbial Diversity ◽  
Water Flooding ◽  
Petroleum Reservoir

scholarly journals Modeling Wettability Variation during Long-Term Water Flooding

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Renyi Cao ◽  
Changwei Sun ◽  
Y. Zee Ma
Keyword(s):  
Oil Recovery ◽  
Water Flooding ◽  
Residual Oil ◽  
Displacement Efficiency ◽  
Oil Saturation ◽  
Residual Oil Saturation ◽  
Polar Substance ◽  
Oil Displacement Efficiency ◽  
Reservoir Wettability

Surface property of rock affects oil recovery during water flooding. Oil-wet polar substances adsorbed on the surface of the rock will gradually be desorbed during water flooding, and original reservoir wettability will change towards water-wet, and the change will reduce the residual oil saturation and improve the oil displacement efficiency. However there is a lack of an accurate description of wettability alternation model during long-term water flooding and it will lead to difficulties in history match and unreliable forecasts using reservoir simulators. This paper summarizes the mechanism of wettability variation and characterizes the adsorption of polar substance during long-term water flooding from injecting water or aquifer and relates the residual oil saturation and relative permeability to the polar substance adsorbed on clay and pore volumes of flooding water. A mathematical model is presented to simulate the long-term water flooding and the model is validated with experimental results. The simulation results of long-term water flooding are also discussed.

scholarly journals Simulation of Formation Damage after Long-Term Water Flooding

2013 ◽  
Vol 2013 ◽  
pp. 1-7
Author(s):  
Liu He ◽  
Gao Yang ◽  
Li Guoxin ◽  
Li Yiliang
Keyword(s):  
Oil Recovery ◽  
Element Model ◽  
Water Flooding ◽  
Permeability Change ◽  
Compression Pressure ◽  
Theoretical Understanding ◽  
Simulation Domain ◽  
Production Wells ◽  
Wellbore Failure

Water flooding is a commonly used technology for enhancing oil recovery. Its main mechanism is to maintain higher pressure to sweep oil towards production wells. However, the strong water flooding will cause higher compression pressure around the injection wellbore. This high pressure in the reservoir causes stress redistribution and higher stress near the wellbore which induces material damage and permeability change. We developed a fluid-solid coupling finite element model to simulate and quantitatively analyze the pressure evolution in the reservoir as well as damage and permeability change in the formation during long-term water flooding process. The obtained results offer theoretical understanding of the benefits (pore pressure increase in the simulation domain), rock damage, permeability change of long-term water flooding, and the insights of how to detect and prevent wellbore failure and collapse due to water flooding.

scholarly journals Model-based production optimization under geological and economic uncertainties using multi-objective particle swarm method

2021 ◽  
Vol 76 ◽  
pp. 60
Author(s):  
Mohammad Mahdi Moshir Farahi ◽  
Mohammad Ahmadi ◽  
Bahram Dabir
Keyword(s):  
Pareto Front ◽  
Particle Swarm ◽  
Oil Price ◽  
Water Flooding ◽  
Economic Conditions ◽  
Economic Uncertainty ◽  
Short Term ◽  
Price Fluctuations ◽  
Multi Objective

Optimization of the water-flooding process in the oilfields is inherently subject to several uncertainties arising from the imperfect reservoir subsurface model and inadequate data. On the other hand, the uncertainty of economic conditions due to oil price fluctuations puts the decision-making process at risk. It is essential to handle optimization problems under both geological and economic uncertainties. In this study, a Pareto-based Multi-Objective Particle Swarm Optimization (MOPSO) method has been utilized to maximize the short-term and long-term production goals, robust to uncertainties. Some modifications, including applying a variable in the procedure of leader determination, namely crowding distance, a corrected archive controller, and a changing boundary exploration, are performed on the MOPSO algorithm. These corrections led to a complete Pareto front with enough diversity on the investigated model, covering the entire solution space. Net Present Value (NPV) is considered the first goal that represents the long-term gains, while a highly discounted NPV (with a discount rate of 25%) has been considered short-term gains since economic uncertainty risk grows with time. The proposed optimization method has been used to optimize water flooding on the Egg benchmark model. Geological uncertainty is represented with ensembles, including 100 model realizations. The k-means clustering method is utilized to reduce the realizations to 10 to reduce the computing cost. The Pareto front is obtained from Robust Optimization (RO) by maximizing average NPV over the ensembles, as the conservative production plan. Results show that optimization over the ensemble of a reduced number of realizations by the k-means technique is consistent with all realizations’ ensembles results, comparing their cumulative density functions. Furthermore, 10 oil price functions have been considered to form the economic uncertainty space. When SNPV and LNPV are optimized, considering uncertainty in oil price scenarios, the Pareto front’s production scenarios are robust to oil price fluctuations. Using the robust Pareto front of LNPV versus SNPV in both cases, one can optimize production strategy conservatively and update it according to the current reservoir and economic conditions. This approach can help a decision-maker to handle unexpected situations in reservoir management.

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