The field-scale design of chemical enhanced oil recovery (cEOR) processes requires running complex numerical models that are computationally demanding. This paper provides an efficient screening platform for the cEOR feasibility study by presenting five artificial neural network (ANN) based models. We constructed 1,100 ANN training cases using CMG-STARS to capture the variation in reservoir petrophysical properties and the range of injected chemicals properties for a five-spot pattern. The design parameters were coupled with the reservoir properties using several functional links to optimize the ANN models and improve their performances. The training cases were employed using back-propagation methods to construct one forward model (Model #1) and four inverse models. Model #1 predicts reservoir response (i.e., oil rate, water cut, injector bottomhole pressure, cumulative oil) for known reservoir characteristics (i.e., permeability, thickness, residual oil saturation, chemical adsorption) and project design parameters (i.e., pattern size, chemical slug size and concentration), Model #2 predicts reservoir characteristics by history matching the reservoir response, and Model #3 predicts project design parameters for known reservoir response and characteristics. Models #4 and #5 predict project design parameters for a targeted cumulative oil volume and project duration time, which is useful for economical evaluation before the implementation of cEOR projects.
The validation results show that the developed ANN-based models closely predict the numerical results. In addition, the models are able to reduce the computational time by four orders of magnitude, which is significant considering the complexity of cEOR modeling and the need for reliable and efficient tools in building cEOR feasibility studies. In terms of accuracy, Model #1 has a prediction error of 5% whereas the error for other four inverse ANN models is about 20–40%. To enhance the performance of the inverse ANN models, we changed the ANN structure, increased training cases, and used functional links, which slightly reduced the error. Further, we introduced a back-check loop that uses the predicted parameters from the inverse ANN models as inputs in the forward ANN model. A comparison of back-check results for the reservoir response with the numerical results delivers a relatively small error of 10%, revealing the non-uniqueness of solutions obtained from the inverse ANN models.
Anadarko Petroleum wants a fleet of at least six vehicles with armor heavy enough to stop AK-47 bullets at its natural-gas project in Mozambique. And it needs them soon. By examining two very different security-risk environments, this paper will illustrate how easily security-related human-rights risks can go unnoticed unless care is taken early in the risk-management process. Oil production at Libya’s Sharara field, the country’s largest, was resuming on 6 September after a valve was reopened on a pipeline shut by an armed group for more than 2 weeks, Libyan oil industry sources said. A third Damen security vessel will be deployed to provide security and other support services to the international offshore oil companies active off the coast of Nigeria in the Gulf of Guinea, in cooperation with the Nigerian Navy.
Woodside has invested in Sapien Cyber, a Western Australian company specializing in the protection and security of critical infrastructure. The TRITON/TRISIS/HatMan malware incident proved that the worlds of process safety and industrial control systems should be looked at holistically, not just from the standpoint of potential cyberthreats. Most businesses understand that data is essential to improving operational performance and that data technologies provide opportunities for more-accurate risk assessment and control of safety-critical systems. Nonetheless, statistics show that the threat of cybercrime is growing. Texas Sen. John Cornyn introduced legislation that would extend authority over the cybersecurity of oil and natural gas pipelines, as well as liquefied natural gas facilities, to the secretary of energy.
Understanding and management of water, be it produced, injected, or for use in drilling and fracturing operations, is critical for our industry. This session reviews selection methods and application of chemical additives to solve problems associated with a range of challenges encountered, focusing particularly on scale and microbiology.
Cyberattacks on energy infrastructure have become a headline affair in recent years, and the costs of not addressing the threats they pose can be catastrophic. What are the responses, and how does the convergence of IT and OT help close the security gaps? Woodside has invested in Sapien Cyber, a Western Australian company specializing in the protection and security of critical infrastructure. The TRITON/TRISIS/HatMan malware incident proved that the worlds of process safety and industrial control systems should be looked at holistically, not just from the standpoint of potential cyberthreats. Most businesses understand that data is essential to improving operational performance and that data technologies provide opportunities for more-accurate risk assessment and control of safety-critical systems.
It has been demonstrated in both laboratory measurements and field applications that tertiary polymer flooding can enhance oil recovery from heterogeneous reservoirs, primarily through macroscopic sweep (conformance). This study quantifies the effect of layering on tertiary polymer flooding as a function of layer-permeability contrast, the timing of polymer flooding, the oil/water-viscosity ratio, and the oil/polymer-viscosity ratio. This is achieved by analyzing the results from fine-grid numerical simulations of waterflooding and tertiary polymer flooding in simple layered models.
We find that there is a permeability contrast between the layers of the reservoir at which maximum incremental oil recovery is obtained, and this permeability contrast depends on the oil/water-viscosity ratio, polymer/water-viscosity ratio, and onset time for the polymer flood. Building on an earlier formulation that describes whether a displacement is understable or overstable, we present a linear correlation to estimate this permeability contrast. The accuracy of the newly proposed formulation is demonstrated by reproducing and predicting the permeability contrast from existing flow simulations and further flow simulations that have not been used to formulate the correlation.
This correlation will enable reservoir engineers to estimate the combination of permeability contrast, water/oil-viscosity ratio, and polymer/water-viscosity ratio that will give the maximum incremental oil recovery from tertiary polymer flooding in layered reservoirs regardless of the timing of the start of polymer flooding. This could be a useful screening tool to use before starting a full-scale simulation study of polymer flooding in each reservoir.
Li, Wai (The University of Western Australia) | Liu, Jishan (The University of Western Australia) | Zhao, Xionghu (China University of Petroleum Beijing) | Jiang, Jiwei (China University of Petroleum Beijing) | Peng, Hui (Beijing Oilchemleader Science & Technology Development Co., Ltd.) | Zhang, Min (Shengli Oilfield Exploration and Development Research Institute) | He, Tao (GWDC Drilling Fluid Company, PETROCHINA) | Liu, Guannan (China University of Mining and Technology) | Shen, Peiyuan (The University of Western Australia)
Biodiesel-based drilling fluid (BBDF) draws considerable attention because biodiesel has excellent environmental acceptability and great potential to provide high drilling performance. There are some investigations reported about BBDF both in laboratory and in the field recently, demonstrating its feasibility. In contrast to traditional petrodiesel and mineral oil, biodiesel has some chemical activity which affects the reliability of BBDF in drilling environment. This paper details the principles and strategies for developing and selecting additives of BBDF. A variety of experimental results obtained by laboratory tests were presented to elucidate the importance of suitable additives for an eligible BBDF. Electrical stability test and centrifuge test were conducted to evaluate the effectiveness of emulsifier. A six-speed viscometer and a high-pressure-high-temperature (HPHT) rheometer were used to measure the parameters of BBDF to evaluate organophilic clays and rheological modifiers. Density test was performed to investigate the suspendability of the fluids. Hot rolling treatment was carried out to study the thermal tolerance of the fluids. The laboratory results and the literature showed that both lime content and calcium chloride concentration have significant effects on the stability and rheological parameters of BBDF. Even moderate amount of lime in BBDF will significantly decrease the stability of BBDF. The effect of calcium chloride concentration on BBDF varies according to the type of emulsifier. A compound emulsifier based on fatty alkanolamides and alkyl sulfonates exhibits reliable ability to prepare stable, thermal-tolerate invert biodiesel emulsion. It offers biodiesel emulsion reduced viscosity compared to those given by traditional Span/Tween emulsifier combinations. For another, commercial organophilic clays cannot give satisfactory rheological parameters because the viscosity-temperature profile of BBDF is often steeper than those of traditional oil based drilling fluids (OBDFs). Therefore, rheological modifier should be used to compensate the viscosity loss of BBDF under high-temperature conditions. A condensate of alkoxylated fatty amine and polycarboxylic acid showed good performance to provide a relatively flat rheological profile. Some empirical laws, principles and strategies are summarized for BBDF additive selection. One is that the combinations of non-ionic and anionic emulsifiers have better effectiveness for biodiesel. The other conclusion is that lime content must be strictly controlled. With the boom of the biodiesel industry, it is predicted BBDF will take a place in the family of drilling fluid. However, most previous works show that BBDF may be not satisfactory when the temperature is over 120 Celsius degrees. This work presents valuable experience for further improvement of this promising drilling fluid.
Wenquan, Tang (Sinopec Research Institute of Petroleum Engineering) | Chao, Xiao (Sinopec Research Institute of Petroleum Engineering) | Yuzhi, Xue (Sinopec Research Institute of Petroleum Engineering) | Tian Lu, Zhang Hongbao (Sinopec Research Institute of Petroleum Engineering) | Chengcheng, Niu (Sinopec Research Institute of Petroleum Engineering) | Ruiyao, Wang (Sinopec Research Institute of Petroleum Engineering) | Qingshui, He (Sinopec Research Institute of Petroleum Engineering) | Lingjun, Kong (Sinopec Research Institute of Petroleum Engineering) | Zhifa, Wang (Sinopec Research Institute of Petroleum Engineering) | Haoya, Liu (Sinopec Research Institute of Petroleum Engineering) | Yan, Li (Sinopec Research Institute of Petroleum Engineering)
In order to solve the problem of severe borehole instability while drilling in the S oilfield, technical research on drilling fluids has been carried out. Firstly, the paper analyzes the mechanism and technical difficulties of borehole instability in depth. Aiming at the reasons of borehole instability, the reasonable drilling fluid flowrate was defined by considering hydraulic erosion, drilling fluid plugging property, inhibition, etc, and the anti-sloughing drilling fluid system was optimized by way of strengthening the plugging and inhibiting properties of drilling fluid system. This technology has been applied in more than 40 wells in the S oilfield, the problem of borehole instability in the fractured formation was solved successfully, and the drilling speed was increased by 25.3%, which greatly reduced the downhole complexity and achieved remarkable application effect.
Liu, Guoqiang (PetroChina Exploration and Production Company) | Hou, Yuting (PetroChina Changqing Oilfield Company) | He, Junling (PetroChina Jilin Oilfield Company) | Zhang, Hao (PetroChina Xinjiang Oilfield Company) | Wu, Jinlong (Schlumberger) | Zhao, Xianran (Schlumberger) | Li, Huayang (Schlumberger) | Wu, Fangfang (Schlumberger) | Li, Shenzhuan (Schlumberger) | Wang, Yuxi (Schlumberger)
Most shale oil resources in China are lacustrine deposit. The reservoirs are usually characterized by complex lithology and high heterogeneity with various mineral compositions (quartz, carbonates, feldspars, pyrites and volcanic ash), total organic carbon and pore structure. How to delineate the shale oil reservoir, how to identify the ‘sweet spots’ and its distribution are the two major challenges and objectives for this study.
To answer the question, a systematic workflow was proposed by integrating the advanced logging technologies (such as nuclear magnetic resonance, micro-resistivity imager, spectroscopy data, array dielectric tool) with special core measurement data. Firstly, the shale oil reservoir was classified into different types according to the logging responses. Secondly, core samples were chosen from each type and sent out to lab for a series of core special experiments to test the microscopic properties. Finally, the advanced core analysis results and logging technologies were integrated to depict the characters of the different types of shale oil reservoirs from microscopic to macroscopic scale. And by comparing with testing data, the features of best shale oil reservoir type can be identified, and the distribution and potential of shale oil reservoir can be unraveled.
The new approach helped to get a thorough understanding of the shale oil reservoirs characteristics, such as lithology, mineral composition, pore types, pore size distribution, oil content, kerogen type and maturity of organic matter, organic carbon content and distribution. Six different kinds of shale oil reservoir facies were classfied from loging responses, inculding super high gamma ray siliceous shale, high gamma ray siliceous shale, high gamma ray argillaceous shale, high gamma ray tuffaceous shale, medium gamma ray siliceous shale and medium gamma ray argillaceous shale. High gamma ray siliceous shale and medium gamma ray siliceous shale are proved to be the best shale oil reserovir, which contains 2~8% of TOC, 2~12% of effective porosity, more than 50% of quartz content and high propotion of macropores.
The method proposed in this project has been implemented in many unconventional reservoirs in china to evaluate the resource potential and get a comprehensive understanding of the shale oil reservoir.
The wells tested based on the recommendation has got promising production after fracturing, which brought client big confidence for future exploration.
Lu, Mingjing (China University of Petroleum, Colorado School of Mines) | Su, Yuliang (China University of Petroleum) | Wang, Wendong (China University of Petroleum) | Zhang, Ge (Xianhe Oil producing Plant, Shengli Oilfield, Sinopec)
Refracturing treatment are performed since stimulation effect won't last for entire life. Screening wells for refracturing needs a systematic analysis of huge amounts of data. With literature review, it is obviously that there are many factors controlling the success of refracturing and factors may vary in different oilfields. Proper factors and data processing are the primary principle in candidate selection. The Integrated Multiple Parameters (IMP) method is presented to provide assists in selecting candidate wells.
After deeply researching over 200 restimulated wells, all factors thought to be related with success of refracturing are listed and analyzed, results show that single factor may have great influence on restimulation but no significant patterns can be obtained since too many factors making things complicated. The IMP method proposes five parameters which are all integrated by those single factors. It is emphasized that all parameters have physical or engineering meanings which makes it easier to quantify their correlation in refracturing. Besides, all the parameters are dimensionless which makes it easier for using in mathematical models and statistical analysis.
The five dimensionless parameters are developed considering the most important aspects of candidate wells selection which are showed as followed: fracture reorientation, well completion, reservoir depletion, production decline, oil-water well connectivity. Parameters are calculated for all the restimulated wells to dig into their correlation with the outcomes of refracturing. A simple decision model is built to help with screening wells for refracturing. Results shows that it is more executable to evaluate and predict the success of refracturing with these dimensionless parameters. Fracture reorientation parameter is the primary one to be considered since it leads to fracture reorientation which brings significant production increment. Then two types of potential wells are picked: (a) wells with dissatisfied initial well completion, low production decline rate and high oil-water connectivity parameter; (b) wells with satisfied initial well completion, high well completion parameter, low production decline parameter, reservoir depletion parameter and low oil-water connectivity parameter for wells that are not easy for fracture reorientation. Wells selected are proved to be refracturing potential which verify the reliability and accuracy of IMP method.
The IMP method is an improved approach integrating most of the important factors which makes candidate selection much more predictable and it succeeds in screening out more than 80% of the potential wells in field test. Also, it can be applied widely in different oilfields since all the parameters are dimensionless. By combining with some mathematical methods such as neural networks, it can even predict increment of the restimulation treatment.