bluuebunny/crossref_metadata_2025_split huggingface dataset:
Alternate Path Horizontal Openhole Gravel-Pack Completion in Soft-Weak Carbonate Gas Reservoir: Offshore East Java
Authors: Firmanto Tri , Aoki Toru , Onggo Indra , Jayadi Agus , Akbari Aulia , Merati Putu Astari , Cerron Dante 
Published: October 2019

Abstract
Increasing natural gas demand in Indonesia has driven many operators to develop potential gas field assets, whether offshore or onshore, across Indonesia. One such field is BC which is located offshore East Java in a tectonically active area and part of the ABC complex. The field is composed of carbonate rock which is globigerinid in nature, with the presence of different facies such as packstone, wackstone and grainstone, of which the latter has the best permeability. An extensive geomechanical study was conducted and one of the conclusions was that solids and fines production to some degree are likely to happen from the carbonates in this field. To minimize the risk of solids production, an openhole gravel pack (OHGP) system was designed and deployed.
Horizontal OHGP involving screens equipped with shunt tubes for alternate packing are commonly deployed in unconsolidated sandstone formations around the world. The use of filter cake breakers, during or after OHGP placement, is regularly included as part of these treatments. The BC is a carbonate field, besides the low frac gradient and the naturally fissured characteristics associated to the rock which makes it prone to high leak-off, the completion strategy required a special designed filter cake breaker inert to the formation and capable of helping to minimize the lift-off pressure; the challenge required a different approach.
The successful completion of these wells required the use of state-of-the art gravel pack placement simulator, special analysis of Bottom Hole data during gravel pack placement and customized gravel pack fluid, capable of transporting proppant and clean the filter cake afterwards.
One deviated and three horizontal wells with 9 5/8-inch casing and average of 8.6-inch openhole diameter were drilled and successfully completed. Gravel pack placement interpretation using bottomhole gauge data indicates full annular packing for all OHGP cases. After completion, wells were started smoothly with no solids production observed.
This paper highlights key technical challenges and risks encountered during the preparation, design, execution, and evaluation stages of this operation and discusses how these challenges were overcome and the risks mitigated. Finally, the lessons learned and their implementation towards the improvement and optimization of future operations are discussed.
Transient Heat Transfer Model for Wellbore and Formation of Shut-In Offshore Oil Wells
Authors: Fang Tao , Liu Yigang , Bai Jianhua , Chen Huaxing , Zhao Shunchao , Li Yanyue , Pang Ming , Wang Yufei , Dong Peng 
Published: October 2019

Abstract
The heat exchange between wellbore and formation is unsteady after the oil well is shut in. As the shut in time increases, the fluid temperature in tubing would decline in a continuous way until it reaches a thermal equilibrium at the ambient temperature. However, there exist the potential risks of wax deposition, crude oil solidifying and poor fluidity in wellbore during the fluid temperature drop, especially for the waxy oil and heavy oil.
For resuming production of the well, the prediction of transient temperature is crucial. Taking account of the heat exchange between the fluid in tubing and formation/seawater/atmosphere for the offshore oil wells, the steady-state heat transfer before shut in is modeled based on heat balance. And the transient model for the shut-in stage is developed on the basis of Fourier's law of heat conduction, which can be solved by use of the finite difference method according to the initial condition and boundary conditions. To investigate the variation of transient wellhead temperature (WHT in short), the dimensionless WHT drop is defined.
For verifying the reliability and accuracy of the model, the wellhead and flowing temperature of a certain offshore oil well is monitored. The actual monitored WHT is 30.5 °C and the simulated value is 30.9 °C during the steady production stage. After shut in, the relative error of the simulated WHT is less than 5%, showing the model is credible. The variation of transient WHT is studied by applying the model as well. The results present that within just a few shut in hours, the WHT decreases rapidly. And then it goes down gradually to the air temperature. The WHT would almost fall to the atmospheric temperature after shut in 24 hours, even though the air temperature and liquid production before shut in differs greatly. The dimensionless WHT drop declines with the increase of water cut and keeps constant when the water cut is more than 40%.
This paper focuses on modeling of transient temperature for the offshore production wells after shut in and summarizes the law of temperature drop in wellbore and formation. It provides an important basis for making the flow assurance plan after the well is shut in.
Acidizing Done Right in Hot Offshore Wells: Case Study
Authors: Nikolaev Max , Kamaletdinov Bulat , Molero Nestor , Payne Courtney , Fernandez del Valle Julia , Daeffler Christopher , Dunaeva Anna 
Published: October 2019

Abstract
Treating deep hot carbonate reservoirs, such as those found in the Arabian Gulf, presents a series of complex and related challenges to achieve effective and uniform stimulation. Due to the elevated temperature and heterogeneous formation, achieving good reservoir contact with an acid system along the entire interval of interest requires robust treatment fluids that can withstand the harsh environment. Recently, a novel single-phase retarded acid (SPRA) system and an engineered degradable large-sized particulate and fiber-laden diverter (LPFD) were introduced in a well in the Arabian Gulf, yielding strong results for the stimulation treatment.
The SPRA, a 15% HCl-based acid system, showed excellent performance in a high-temperature environment (320°F). The fluid delivered similar friction pressures to unmodified 15% HCl, wormholing performance equivalent to emulsified acid without encountering the issues of fluid quality with respect to emulsion stability, and much higher dissolution power than organic acids and chelating agents. The pressure drop after the first acid stage was over 1,000 psi in about 60 min. After the second stage of acid, the pressure drop was close to 1,000 psi in about 30 min.
Previous stimulation jobs in the region indicated a need for a significant amount of traditional diversion materials to achieve an effective plugging of the leakoff zones. A novel degradable LPFD system was introduced, achieving a significant increase of injection pressure (~1,000 psi) across the perforations. In addition to the effect on the diversion pressure, the implementation of the LPFD system has helped to reduce the footprint in offshore operations, has simplified materials handling, and has delivered the most efficient diversion performance in bullhead operations compared to other diverters.
This article presents a novel method of stimulating deep hot offshore wells by combining an efficient SPRA and a unique degradable LPFD. These methods represent a step change to current practices and can be considered for effective stimulation in challenging carbonate formations.
A Novel Method to Characterise Time-Variation of Reservoir Properties: Experimental Study, Simulator Development and its Application in Bohai Bay Oilfield
Authors: Sun Zhaobo , Li Yanlai , Ma Kuiqian , Xu Jianchun , Zhang Guohao , Jiang Ruizhong , Pan Shaowei 
Published: October 2019

Abstract
For waterflooding oilfields, both the lab experiments and field practices have proved that the physical properties of water-flooding reservoirs would be altered due to the washing of injected water. This condition has not aroused enough attention. There is no proper approaches to describe the change of reservoir parameters against water flux in reservoir simulation. Most commonly used reservoir simulators (Eclipse, CMG, et al.) neglect the alteration of reservoir properties during simulation, and thus, lead to unreasonable history matching and production forecasting.
A new parameter known as Pore Cross-sectional Area Flux (PCAF) is introduced to continuously characterize the time-variation of a property during simulation. This new method overcomes the disadvantage of the previous characterization approach known as Pore Volume (PV), which is strongly dependent on grid size.
A new numerical simulation software in which reservoir properties are considered functions of PCAF is developed based on the black oil model, and the new simulator is validated against Eclipse. Furthermore, the effects of the time-variation of different parameters on the ultimate oil recovery are investigated. Finally, this simulator is applied to SZ-I oilfield in Bohai Bay to demonstrate how this simulator can achieve more accurate simulation.
Accounting for Adiabatic Expansion in Analyzing Warmback Temperature Signal After Cold-Fluid Injection
Authors: Hashish Refaat G , Zeidouni Mehdi 
Published: October 2019

Abstract
Temperature transient analysis has been evolved as a new alternative that can be adopted jointly with pressure transient analysis for reservoir characterization and surveillance purposes. In this work, an analytical approach is developed to characterize the reservoir using down-hole temperature measurements obtained during a pause in injection activity. The analytical solution is developed by solving mass conservation equation coupled with energy balance equation, which are subject to appropriate initial and boundary conditions. The solution is obtained using Hankel integral transformation to evaluate the temperature response with respect to time and space. The obtained solution identifies and evaluate: (i) the early-time cooling effect caused by adiabatic expansion of injected fluid in injection zone after injection stops and, (ii) late-time warm-back effect caused by heat flux from cooled unswept region and the surrounding cap/bed strata. Using early- and late-time asymptotic solutions, temperature inversion procedures are introduced in the form of appropriate graphical techniques to characterize the reservoir. Measured sandface temperature after injection is stopped along with the developed procedure are used for evaluating thermal properties of reservoir such as effective heat capacity and thermal conductivity, pressure diffusivity of the reservoir, extent of thermal front and initial geothermal reservoir temperature. The analytical solution results are validated against numerical results obtained via a thermally coupled numerical reservoir simulator. The analytical solution provides good agreement with the numerical results during forward modelling and inverse modelling. Sensitivity analysis is developed to investigate effect of wellbore storage, characteristics of reservoir and injection rate on the temperature behavior during shut-in.
Deep Autoencoder-Derived Features Applied in Virtual Flow Metering for Sucker-Rod Pumping Wells
Authors: Peng Yi , Zhang Jianjun , Xiong Chunming , Shi Junfeng , Zhao Ruidong , Zhang Xishun , Xu Dongping , Li Qiming , Deng Feng , Chen Shiwen , Liu Meng , Chen Guanhong , Wang Cai 
Published: October 2019

Abstract
With the depletion of reservoirs, it is inevitable that once very prolific conventional and unconventional wells become stripper wells characterized as producing no more than 35 barrels of liquid equivalent per day over a 12-month period. The conventional metering strategy is not economical for its huge investment in facilities, equipment, sensors, and ongoing maintenance compared to current low production. This paper presents an innovative method utilizing state-of-art artificial intelligent algorithms to predict the production rate from real-time IIot testing and producing data with very low cost and reliable accuracy.
Abundant real-time field and well data acquired from IIot and digital field facilities establish a fundamental foundation for developing a machine learning application. This paper presents a method to predict the real-time production rate from real-time IIot data. In our method, we start with constructing our datasets from different data sources by combining the dynamometer cards, pumping stroke and rate, pump, rod, wellbore and reservoir parameters as inputs and the corresponded production rate as targets. The machine-learning model contains two neural networks: first, a deep autoencoder to extract the feature representations from all the dynamometer cards, then another neural network combining all related features to predict the real-time production.
The deep autoencoder derived features from dynamometer cards are used as parts of inputs to further real-time production prediction models, which eliminate the disadvantage of conventional hand-crafted features. Hand-crafted features can lose important information whereas autoencoder is designed to minimize information loss by learning high level features that can be used to reconstruct the cards. The production prediction model with pump and producing data combining more informative abstract features generate good accordance with the history data. After tested testing and validating data in several fields in one operator’s fields in China, the model demonstrates very high accuracy and with R2 more than 0.92, MAE less than 0.5 of wells producing less 5m3/day, RMSE less than 1.6 of wells producing 5-10m3/day and RMSE less than 2.2 of wells producing more than 10m3/day. The model has also been tested on hundreds of newly producing wells and with error in 10%, compared with high resolution real-time metering equipment.
The method described in this paper can be fully utilized to metering the real-time production with ultra-low cost in wells as long as acquiring a real-time dynamometer card. With the fast development of artificial intelligence technology and expanding training datasets, artificial intelligence is a good choice to lower the investment and maintenance cost for conventional and unconventional fields in the low oil price trend.
Ultra-High Density Oil-Based Drilling Fluids Laboratory Evaluation and Applications in Ultra-HPHT Reservoir
Authors: Li Jiaxue , Li Qinghui , Li Ning , Teng Xueqing , Ren Lingling , Liu Hongtao , Guo Bin , Li Shaoxuan , Hisham Nasr-El-Din , Al-Mujalhem Manayer 
Published: October 2019

Abstract
Global energy demand has driven petroleum industry to develop hydrocarbon resources from extremely harsh formations. Ultra-high density drilling fluids are critical to successful drilling and completion practices in all of these wells. In this paper, potential weighting materials were systematically evaluated and screened to accomplish an ultra-high density oil-based drilling fluid system (19.62 to 22.12lb/gal) aimed to utilize in ultra HPHT conditions (&gt;30000psi and &gt;410°F).
Potential high-density weighting materials were evaluated. Properties (pure density, particle size/distribution, surface area etc.) were evaluated and compared. Special treatment was conducted to optimize properties of weighting materials. HPHT filtration tests under static and dynamic conditions were conducted at higher than 410°F and 300 psi. Real cores with an average porosity of 19% and an average permeability of 50 md were used in the filtration tests. Rheological properties, sag tendency, the volume of filtrate, and the filtrate cake characterization was measured before and after heating at 410°F for 16 hours.
Results revealed that ultra-micro manganese and ilmenite complex after suitable surface treatment could act as an ideal weighting material than ultra-pure barite or other materials, which could fail in rheology and sag measurement with such high temperature and density. Viscosity and filtration analysis confirmed the stability and reliability of this novel ultra-high density oil-based drilling fluid.
This study developed a challenged drilling fluid system under critical conditions, as well as established a systematical laboratory evaluation and screening procedure of weighting materials and contributed recommendations on how to utilize it in the fields.
Low Pore Pressure Hydraulic Fracturing Breakthrough in Sanga-Sanga: Simple Methods in Performing Hydraulic Fracturing in Low Pore Pressure Reservoir
Authors: Rachmanto Rian , Pasaribu Hendra , Widjarnako Andre , Halinda Debby 
Published: October 2019

Abstract
Pertamina Hulu Sanga-Sanga is operator of Sanga-Sanga block located onshore of the Mahakam Delta, East Kalimantan Indonesia that has been producing since 1970's. With recovery factor to date is approximately of 70% of its initial in place, hence Sanga-Sanga block has entered maturity. However much of remaining reserve is still locked in reservoir with lower permeability where conventional completion cannot economically produce these type reservoirs. Many technologies have been applied in order to produce at economical rate these reservoirs, including hydraulic fracturing.
Hydraulic fracturing has been applied in Sanga-Sanga since 1980 until 2005 as first campaign but faced with many failures amounting 85% of the job failed. After a thorough study in 2006, one of the finding of contribution of failed job is high fracturing pressure triggered by high frac gradient. The study suggests that hydraulic fracturing reservoirs candidates should go through depletion to lower the pore pressure and lowering the frac gradient in process. By applying this method the second campaign had been executed from 2007 until 2012 with varying results.
Several failed jobs were identified as result of inability of the well to recover most of frac fluid in formation due to reservoirs have been very depleted with pore pressure below 2.5 Ppg. From this finding it is deemed that reservoirs with pore pressure less than 2.5 Ppg are not suitable as hydraulic fracturing candidates and therefore losing opportunity in producing depleted reservoirs.
In 2015 another attempt on executing hydraulic fracturing in depleted reservoir (pore pressure of 1.89 Ppg) was done. By addressing fracturing design, fracturing execution and sand clean out and Nitrogen (N2) unloading post hydraulic fracturing job resulted in successful job. The result was well was able to increase its production by 4 fold.
This paper illustrates the approaches in hydraulic fracturing in low pore pressure reservoirs (less than 2.5 Ppg) that usually are excluded as hydraulic fracturing candidates. This paper also discusses the challenges in hydraulic fracturing that comes with the typical reservoir characteristic in Sanga-Sanga and solution addressed in overcoming these challenges to achieve the successful hydraulic fracturing job especially in low pore pressure reservoirs.
Artificial Intelligence Assisted Decision Support Center: Pilot Implementation in Onshore Indonesia
Authors: Pratama Raka Cahya , Siregar Raynold , Putra Adriyan , Wicaksono Arief Randy 
Published: October 2019

Abstract
For years, the oil and gas industry has been utilizing real-time sensors to monitor multiple parameters. In drilling operations, these sensors are highly important in achieving the well objectives. They provide data to guide the well execution and aid during the evaluation phase. The downside is the limited capability to identify operational anomalies. The latest popular strategy to mitigate this downside is using a Decision Support Center to obtain the most benefit from this data. Decision Support Center should be available for 24-hour operations and consists of multiple personnel to review data, provide path forward recommendation, and alert the field supervisor.
During these past years, most companies have optimized the number personnel to keep competitive in a low oil price environment. However, some knowledge has been lost during the process. On the other hand, the industry worldwide is entering an era of digital transformation. This triggers the need for artificial intelligence systems that can translate analog knowledge from personnel to digital data, analyze for execution anomalies from sensor readings, and provide feedback and recommendations to the end-users.
In one of largest mature onshore Indonesian blocks, a pilot implementation of artificial intelligence assisted Decision Support Center was developed. With limited time and cost, the project needed to be developed as fit-for-purpose. Thus, the system focused on the significant problem which historically caused million dollars in lost opportunity in the form of stuck pipe. A single stuck pipe event could result in a US$ 2.5 MM loss, which is more than 2 times the typical well AFE in this block. Beside surface and downhole sensors readings, subsurface prognosis, torque and drag model; operational best practices were also included in the system. Anomaly alarms were developed, including ECD limit by depth, pick up weight limit by depth, torque limit by depth, potential loss circulation zone, maximum allowable static time, and maximum allowable pumps off time. Whenever the sensor reading exceeds these limits, an automatic alarm would be generated and sent to the field supervisor, drilling superintendent and drilling engineer. As result, it only required 1 personnel per 4 rigs to maintain the process compare to 3-4 personnel per rig required with the conventional Decision Support Center process. This process successfully eliminated stuck pipe events though to the remaining of the drilling campaign of 56 wells, where the historical frequency had been 1 stuck pipe event out of 20 wells.
Future improvement in this system will utilize machine learning to develop anomaly alarms by gathering data from offset well operations. An additional benefit of this system is to implement it in workover operations.
Infill Well Placement Optimization Using Integrated Asset Modeling Technique
Authors: Lee Taeyeob , Jeong Daein , Jang Sangyup , Kim Junggyun , Mo Cheolhoon , Jeong Hoonyoung , Choe Jonggeun 
Published: October 2019

Abstract
Determining optimal infill well placements is a complex problem that depends on reservoir properties and specifications of well and surface network. A numerical simulation is often the most appropriate method to evaluate the feasibility of the candidates. An integrated asset model of A field in the Middle East is built that couples a subsurface reservoir model with a surface network model. The integrated asset model is used to find optimal locations of 10 infill wells which are scheduled to drill in the future.
This paper proposes a step-wised approach for finding multiple infill well locations considering constraints of surface network. Firstly, an optimization process is conducted for all infill wells using an evolution strategy. Next, the same process is repeated exclusive of some wells, whose locations are already determined from the 1st optimization. This step improves an efficiency of the optimization and therefore, gives increased cumulative oil production results. Finally, integrated asset models are constructed for the 5 best cases, and elevation profiles of flowlines and trunklines are extracted from a geographic information system (GIS) at this time.
The optimal well locations are quite far from previous producing wells. It is good for avoiding production interferences, although these locations have negative impacts on delivering produced fluid to a facility because of pressure losses. The integrated asset model could evaluate several effects simultaneously and could give practical infill well locations for the target field.