Search

Traditional production logging uses cable or coiled tubing for productivity measurement. Such measurement normally requires well to be shut-in, which brings risks for field operation, especially for directional or horizontal wells; it affects normal field production management. Besides, the result only reflects production profile at one time point. The later production system adjustment or changes of water production value need to be measured again, eventually increasing the total cost. Productivity monitoring technology based on ‘Quantum Dot’ tracers uses nano-size quantum dots to make micron-size quantum signature codes or marker-reporters. As the basic monitoring particle, the quantum signature code can be made to flake quantum dot monitoring tape through polymer materials, this special tape is wrapped around pipe or screen and placed at target location in the borehole. For different layers and fluid phases, quantum monitoring tapes with different codes and affinity properties are utilized to distinguish them. When monitoring tapes come into contact with different fluids such as oil or water in formation, diffusion channels will be generated, from which quantum monitoring particles (marker-reporters) are released and adsorbed on the surface of the material. As fluid flows, quantum monitoring particles in monitoring tapes will be continually released and adsorbed on tapes surface and carried to the wellbore, this achieves a release process proportional to flow rate. The produced liquid collected at wellhead is mixed with quantum monitoring particles with various codes, which can be separated by laboratory analysis. By counting the percentage of marker-reporters with different codes, the production rate percentage of different intervals can be obtained, and then for each stage, oil, gas, and water production can be obtained according to the total wellhead production. The quantity of quantum monitoring particles is massive, and its release rate is in a positive correlation to flow rate. Under normal circumstances, unlimited production monitoring can be achieved within 3 years. Traditional production logging measure formation and production parameters such as temperature, pressure, density, resistivity, flow rate, water cut etc. logging tools and packers are combined to measure flow volume from each stage and fluid types are identified at wellhead. Main disadvantage of this method is the requirement for wellbore shut-in and the risk of unsuccessful RIH the tools as the wellbore faces common issue – wellbore deformation. In addition, it is not normal using packers to isolate other zones while allowing only one stage to produce. Also, production logging can only obtain inflow profile at a specific time or short period of time. If one needs to get information such as later production data or water cut value when producing system is adjusted or changed, logging operation must be done again. It results in higher costs. How to monitor production profile of each stages any time during normal production process and utilize these data to make timely adjustment is of great significance in terms of operation and efficient development of single well or for a whole block.

The diversification of energy forms and the access of more intelligent distributed devices such as energy storage units have caused the explosive growth of grid system information. Therefore, this paper proposes a method of electric energy management based on binary genetic algorithm. The binary genetic algorithm is used to optimize the energy management scheme, so as to ensure the comfort of electricity consumption and reduce the power cost. Finally, the effectiveness of the proposed method is verified by comparing the cost and comfort of different methods through simulation examples.

With the transformers heavy using, efficient and reliable network and transportation protocol are becoming more and more important to collect energy data from the transformers. This paper proposed a new network topology for data collection from large amount resident transformers. This topology could provide flexible access service to user and improve network scalability. This paper also proposed a new data transferring protocol based on SNMP. The messages are classified into three types and encapsulated into trap packets. With an add-on acknowledgement mechanism, the new protocol could guarantee the delivery of important messages and merge other messages. It improved the utilization of the data collection network.

Federated Learning (FL) has been an emerging trend in machine learning and artificial intelligence. It allows multiple participants to collaboratively train a better global model and offers a privacy-aware paradigm for model training since it does not require participants to release their original training data. However, existing FL solutions for vertically partitioned data or decision trees require heavy cryptographic operations. In this paper, we propose a framework named FederBoost for private federated learning of gradient boosting decision trees (GBDT). It supports running GBDT over both vertically and horizontally partitioned data. Vertical FederBoost does not require any cryptographic operation and horizontal FederBoost only requires lightweight secure aggregation. The key observation is that the whole training process of GBDT relies on the ordering of the data instead of the values. We fully implement FederBoost and evaluate its utility and efficiency through extensive experiments performed on three public datasets. Our experimental results show that both vertical and horizontal FederBoost achieve the same level of accuracy with centralized training, where all data are collected in a central server; and they are 4-5 orders of magnitude faster than the state-of-the-art solutions for federated decision tree training; hence offering practical solutions for industrial application., Comment: 15 pages, 8 figures

The sensitivity of energy ratio method varies with the size of time window. We propose a multi-time window energy boundary detection method which improves the picking accuracy for data with a low-to-medium signal to noise ratio (SNR). The multi-time window algorithm effectively improves the system reliability of the energy ratio method. Through the distribution of characteristic values in different time windows, the picking results of low signal-to-noise ratio data can be effectively deleted. Then, a small-step fitting algorithm is applied to the remaining first-arrival characteristic values to obtain the final characteristic value evaluation. Based on the retained first-arrival characteristic values, the missing values were assigned by interpolation, then map the result on the original record and finally, first-arrival picking was completed by using a small time window. We test the performance of each module to prove the validity of the proposed methods. Finally, we design and develop auto-picking system, and the application shows that the accuracy of picking up can meet the needs of production.

Summary An oil field in Xinjiang, China, experienced a casing failure rate of 15 to 30% in thermal wells, mainly relating to inadequate protocols of casing design. This paper presents a new strain-based casing-design method. New material parameters are proposed to build safety-evaluation principles throughout the service life of a thermal well. In addition, a gas-tight thread joint is applied to prevent steam leakage that otherwise would cause a large transversal stress between different formations, and result in slip deformation of the casing string. Field practices have shown that the new method's fitness works better for thermal wells than previously used methods.

In order to solve the problem of uniform and non-uniform seismic data interpolation, the proposed method converts the data into curvelet domain and carries on the gaussian sampling, then regards the data recovery as an inversion problem which can be solved by using the minimum total variation method. Finally, the interpolated data can be obtained by inverse curvelet transform. The theoretical data processing shows that the algorithm has better interpolation effect for uniform and non-uniform missing data, and the latter is better. In order to further verify the validity of the algorithm, the actual data of a region are used for interpolation processing. The results before and after interpolation show that this method is a fairly good interpolation algorithm.

This paper focuses on the strain based design and field application of thermal well casing for cyclic steam stimulation process. The heavy oil is a main field of China petroleum industry, where the cyclic steam stimulation process has been widely used and playing the dominating role in production. Generally the casing damage rate is 15-30% under this process, which has resulted in a large economic cost. The high damage rate is mainly caused by the current strength design method, where both the room and elevated yield strength were considered not beyond anticipated field thermal stress. In fact the casing material will serve in cyclic thermal elastic-plastic deformation state and the single yield strength is not sufficient for long term thermal stimulation process.This paper presented a new strain based design method for thermal casing string. New material parameters were proposed to build the safety evaluation principle throughout the service life. For thermal casing the material plasticly deforming limit, called as allowable strain, is determined by the homogeneous deforming capacity. For design strain, the material creep rate equation is introduced to evaluate the accumulative elevated strain in long term service together with initial install strain, thermal strain and soil strain. When the design strain is not more than the allowable strain the casing material will safely serve throughout the whole life. In addition the strain fatigue limit is measured to evaluate the material safety for thermal cycle life. According to the factual field engineering environment the gas tight thread joint was adopted to prevent steam leak which otherwise will cause a large transversal stress between different formations and result in slip deformation of casing string.Before the engineering operation the full scale test procedure was proposed and finished to evaluate the string integrity in multiple thermal cycles. From 2011, this method was used in Xinjiang oil field for eight wells for more than 14 steam cycles and all the experiment wells served well without any damage. Several wells were cyclic measured through multi arms inspector and the data showed that all the casing deformation located in controlled scope except that only one has obvious deformation because poorer cementing quality. The field practice has showed that the new method has better fitness for thermal wells.

Abstract Field investigation and failure analysis on casing damage were conducted for cyclic steam stimulation thermal wells in Xinjiang oil-field of China. Evaluation demonstrated that stress-based casing design only meet the requirements of drilling and completing operation, but could not accommodate sufficient security for cyclic thermal production. Although casing failure seldom appeared during drilling and completing, lots of its failures happened within the following production stage. These results indicated that the service environment during this production is the dominant factor affecting casing design and material selection. Failure analysis displayed that there are several typical modes, including deformation, necking, shear, crack and connection parting. These typical modes revealed that those casing experienced obvious plastic deformation during production. Accordingly, strain-based design is proposed in which characteristics of deformation behaviors are taken into account, such as plastic deformation, hardening, creep, stress relaxation, bauschinger effect and strain fatigue limit. Two criterions were determined for this design according to plastic capacity and strain fatigue limit of casing material, respectively. Moreover, one of these criterions had been verified through 8 wells experiments after three thermal cycles. Strain-based design aims to present sufficient axial plasticity capacity beyond elastic limit, before ultimate necking and tensile fracture. It is necessary to consider attached measures for integrity of thermal wells. For thread connection, sufficient sealability is recommended to prevent steam leakage, otherwise which could greatly promote shale's expanding and then result in shear failure in casing. As for the pipe ends, external upset or additional hardening process is suggested to apply to maintain the integrity of thread connection area.