bluuebunny/crossref_metadata_2025_split huggingface dataset:
Use of 4D Seismic To Boost The Profitability Of Infill Drilling In An Offshore Sandstone Oil Field
Authors: DARAMOLA Babalola 
Published: June 2017

Abstract
This paper presents how 4D seismic was used to boost the profitability of an infill production well (XA) in Field X located offshore Nigeria. Field X has an anticline dome structure with sizeable faults and turbidite sandstone reservoirs. It had under-saturated oil at initial conditions, and has been developed with 4 subsea production wells and 2 subsea water injection wells tied back to a leased FPSO vessel.
An Eclipse simulation history match model was constructed in 2012 to support the infill production well proposals XA and XB. The simulation model estimated the oil recovery from infill well XA as 1.57 MMSTB, which was deemed uneconomic. A review of the 2012 simulation model used for the recovery assessment suggested that the XA area was swept by a nearby water injection well (W1). This did not agree with the 4D seismic data. The simulation model water cut in a nearby production well (P1) was also higher than the actual water cut.
It was concluded that the simulation model did not represent actual reservoir performance. The simulation model was optimised by improving the XA infill well path penetration in the target reservoir formation. The connectivity between the W1 water injection well and the production wells was also evaluated. A seismic section between W1 and P1 showed a potential flow baffle between the wells. This baffle was added to the simulation model to delay the water between W1 and P1. Production data suggested that W1 was most likely connected to another production well (P3) via a high conductivity channel. The channel was added to the simulation model to divert most of the water from W1 to P3. These actions improved the P1 water cut and 4D seismic water saturation difference history matches, increased the XA infill well oil recovery by over 50%, and made the well economic.
This paper presents a standard method of how 4D seismic data was used to support infill well planning, and can also be used to justify 4D seismic data acquisition. It is recommended that reservoir simulation models are history matched with 4D seismic and other geologic and production data prior to using the models for prediction and well placement. In this case study, 4D seismic data was used to improve the simulation history match and boost infill well economics. 4D seismic can also be used to locate sealing faults, evaluate fault seal breakdown, find infill well locations, and improve oil recovery.
Introducing a Universal System Design and Workflow for Efficiently Capturing and Managing Geological Modelling Data Assets
Authors: Ibrahim Mohamad A. , Bin Mahfoodh Abdulelah , Hawi Maan 
Published: June 2017

Abstract
Recently, the oil and gas industry witnessed an increased demand for executing complex and large-scale drilling activities that require accurate understanding of subsurface conditions and precise geological observations. To accomplish this, three-dimensional geological modelling is commonly used to accurately define sub-structural and physical properties in the areas of interest. Moreover, geological models are used as input to reservoir simulators to predict underground fluid behavior and ultimately to identify the most efficient, sustainable and economic hydrocarbon recovery scenarios. A geological model is a computerized 3D representation of the earth crust and subsurface based on a set of geological and geophysical properties and is generated using various computer applications.
Over the past years several geo-scientific software technologies were developed to address this increased demand of geological modelling. However, existing commercial geological modelling applications are unable to provide a systematic approach to manage and control various workflows and data assets generated during and after the modeling process. Occasionally, professionals encounter loss of geological modeling projects or the input data used to generate them or even their metadata because there exists no solution to manage and archive this important data asset. Furthermore, practical surveys show that there is also a need for a full dynamic data integration solution to optimize and streamline different processes and activities related to geological models and conducted by geologists, geophysicists, and reservoir engineers.
This case study presents Saudi Aramco's innovative approach of in-house designing and implementing a system to capture and manage geological modelling data assets regardless of the vendor application used for generating them. This system captures geological models projects and their input data with enforcement of a proper data classification and provides archival, tracking, and retrieval workflows across different stages. Additionally, the system provides an interface enabling professionals to search captured geomodels by their respective metadata such as date, well name, reservoir, model type, etc. This new data management system plays a significant role in streamlining geological models data integration while improving data quality and productivity of geoscientists and engineers by providing efficient access to data assets.
Identification and Characterization of Thermally Induced Fractures Using Modern Analytical Techniques
Authors: Almarri Misfer , Prakasa Bona , Muradov Khafiz , Davies David 
Published: June 2017

Abstract
Thermally Induced Fractures (TIFs) are common in waterflooded fields where the injection of (relatively) cold water leads to a cooling front that reduces the formation's in-situ stresses. TIF initiation and growth can thus occur when the previously measured, fracture propagation pressure is not exceeded. The presence of TIFs severely distorts the flood front, decreasing sweep efficiency. This paper applies several published, waterflood analysis methods to TIF characterization in synthetic and real case studies.
These methods include well injection history data using modified Hall analysis, injectivity index and pressure vs. rate analysis, etc. to identify the onset of TIF, its propagation and its properties. The Capacitance Resistance Model (CRM) is chosen to quantify the change in inter-well communication due to TIF, the likely TIF direction and its impact on the flood front. Application of these models is illustrated and verified using reservoir geomechanical/fluid flow simulations. In addition, a field case study is used to demonstrate the value of integrating analytical and semianalytical models when developing an improved understanding of TIF evolution in waterflood operations
Results from synthetic examples using the proposed analytical models confirm that the models correctly identify the onset, monitor the evolution of TIF, and provided valuable insights into the overall well injection performance. The CRM model quantified the connectivity between well pairs, identified TIF initiation and its subsequent impact on well connectivity and flood efficiency. The same techniques are used to analyse data from a real-field case history. TIF initiation and propagation events were clearly identified, even when their existence was much less certain with the other techniques. A correlation between the injection water temperature and the TIF growth dynamics was observed while the well production data and FMI images supported our analysis.
The novelty of the presented approach is in efficiently integrating the recent, analytical and semianalytical models to identify onset, propagation, characteristics, and impact of TIF from the generally available, well injection production history data. The practical workflow employed here will help engineers detect and monitor TIFs; as well as evaluate the metrics describing waterflood performance, namely flood efficiency, inter-well communication and pressure maintenance.
The Use of Artificial Neural Networks to Quantify the Effect of Formation Damage on Well Production Response
Authors: BuKhamseen Nader Y. , Ertekin Turgay 
Published: June 2017

Abstract
This paper presents a workflow that evaluates whether the production rate decline or abnormal pressure behavior is attributed to formation damage. The workflow uses artificial neural networks (ANN) as the engine behind the evaluation process. All the training and validation data comes from a reservoir simulator. The required parameters that are used for building the neural networks are the completion factor (RF) and skin. These parameters are then used to match the production and pressure profiles of the subject well.
Formation damage refers to the reduction of the effective permeability near the wellbore. There are several causes of formation damage including but not limited to the completion and workover fluid, fines movement, and scale deposition. In this paper, the effect of plugged perforation sets and skin are examined. If the reservoir simulation model has a suitable history match, the model response should not considerably deviate from the real well response. If that deviation occurs, the developed ANN is introduced to check if that deviation is a result of formation damage. The reservoir simulator is used to generate several data sets with variable completion factors (RF) and skin parameters to be used for training and testing the ANN. The RF and skin can vary through time to reflect the actual changes in production response. The ANN then outputs the RF and skin factor based on the observed pressure and production profiles. The recommended output of the ANN is eventually validated with the reservoir simulator.
This workflow has been tested on a synthetic, heterogeneous reservoir model. Results show good prediction capabilities for the developed ANN in terms of producing formation damage parameters that correspond the simulated data. The workflow also suggests which parameter (the RF factor or skin) should be updated in the reservoir simulation model to reflect the observed production response.
The results indicate that the data for the subject wells in the reservoir simulation model can be updated in a fast and efficient way using ANN. The ability to vary the number of layers, number of neurons, learning rate, and training algorithm makes the ANN a suitable tool for tackling problems where the relationship between parameters is difficult to comprehend.
Probabilistic Performance Forecasting in History Matching of Low Permeability Reservoirs
Authors: Zhang Xuejiao , Xue Yongchao , Ding Guanyang 
Published: June 2017

Abstract
Since conventional history matching aimed at fractured horizontal wells in low permeability oil reservoirs is affected by a number of factors, such as permeability, fracture half-length, conductivity and so on, there often exists ambiguity in production matching. That is to say, when showing the same curves and results, we cannot make a definite decision to judge which parameter displays the matching results. In this paper, Markov Chain Monte Carlo (MCMC) and AM algorithm are presented to improve history matching and then to obtain more accurate probabilistic production forecasting using actual decline production data. First, the AM algorithm, having an advantage of updating parameters simultaneously and constituting a proposal distribution at each new iteration according to the covariance matrix of the previous iterations over the Metropolis-Hasting (MH) algorithm, is employed to gather field production decline data. Furthermore, MCMC method is utilized to develop a Markov Chain, a stochastic process with a series of various parameters and later value usually only related with the most-recent value. Finally, based on this, the history matching is improved and further probabilistic production prediction P10, P50 and P90 are achieved.
The results indicate that compared with MH algorithm, the AM algorithm can get a greater acceptance ratio. The Markov Chain for production decline data parameters shows a satisfying mixing. The probabilistic cumulative oil production of P10, P50, and P90 is established for target oilfield in this paper. The curves of production rate versus time and cumulative oil production versus time show that the well-established Markov Chain can successfully match the production decline data and then perfectly predict probabilistic production. The novel point in this paper is that a much more effective AM algorithm substituting for the MH algorithm is adopted to form the Markov Chain to improve history matching. The results manifest that MCMC method has the ability to enlarge the reliability of production forecasts, which has a significant influence on reservoir understanding and management.
Dynamic Characterization of Different Reservoir Types for a Fractured-Caved Carbonate Reservoir
Authors: Yong Li , Qi Wang , Baozhu Li , Zhiliang Liu 
Published: June 2017

Abstract
Understanding reservoir types or reservoir patterns is critical for a successful development strategy decision in carbonate reservoirs. For the fractured-caved carbonate reservoirs in china, reservoir types are especially important because different reservoir types may apply different development strategies. This paper propose a systematic method of dynamic characterization on a carbonate reservoir in China.
The proposed systematic dynamic characterization method mainly includes production data analysis and well test analysis, which combined with geological understanding. It is applied to the Ordovician fractured-caved carbonate reservoir in China, which has different reservoir types developed. Different reservoir types are classified and identified, and three of them are illustrated in detail.
Based on the geological features of K fractured-caved carbonate reservoir in China, forward modeling method is firstly used for identification type curve generation of different reservoir types. Different numerical reservoir models are built, and the type curve of well test and rate transient analysis are generated. And the results are used for the actual reservoir type identification. Then combined with geological understanding, reservoir properties and reservoir types are evaluated based the dynamic methods, which include well test analysis and rate transient analysis method. Three reservoir types, which include volumetric caved reservoir, fractured reservoir, fractured-vuggy reservoir, are characterized based on the proposed methods and presented in detail. More than one hundred of reservoirs are evaluated. It is found that OOIP of most reservoirs are lower than 200 thousand cubic meters, and skin factor of most wells are lower than zero.
The understanding of reservoir types and dynamic characterization results are much valuable for the next development options decision, which are applied to the K fractured-caved carbonate reservoir with successful results.
Applications of High-Resolution LWD Resistivity Image Logs for Carbonate Reservoir Characterization
Authors: Wang W. H. , Thagafy M. M. 
Published: June 2017

Abstract
Logging while drilling (LWD) resistivity imaging was typically deployed to provide real-time LWD images to identify critical geological information, e.g., bedding dip changes, lithology changes and large faults to allow optimum geosteering. During the past decade, there has been a progressive increase in the along hole resolution of LWD images, and today's highest resolution tools achieve nominal along hole resolutions of approximately 0.5-in. with full 360° azimuthal borehole wall coverage.
The focus of this study is the high-resolution LWD resistivity images recorded downhole as the memory mode data and their direct comparison with images from conventional open hole ("wireline") resistivity images, to illustrate the similarities and differences between images from the two technologies for fracture characterization and vuggy porosity partitioning in carbonate reservoirs.
Fracture types, distribution and their orientation can be determined from LWD image logs. Proportion of vuggy porosity can be estimated from LWD images by applying porosity-partitioning technique. This study shows that the images generated from the new generation of high-resolution LWD resistivity imagers have sufficient effective along hole resolution to offer an alternate to the conventional open hole images for carbonate reservoir characterization.
ROP Enhancement and Drilling Time Optimization for Long Horizontal Sections in Tight Gas Formations Utilizing MPD Systems – A Case History
Authors: Han Kyungnam , Alexeyenko Alexey , Chavarria Marcos , Markabi Mazen 
Published: June 2017

Abstract
An exploration well was commissioned to evaluate a potential tight gas reservoir by drilling a combined curve and horizontal section while facing a narrow mud weight window (NMWW). Positioned below an anomalous formation, a high probability of influx, losses and stuck pipe scenarios prevailed, coupled with a very low ROP scenario. Also, being a rather long combined curve and lateral section, there was a high risk of caving after drilling, which could disrupt running the liner.
To land the well on target without having any undesirable effects, it was critical to maintaining correct pressure profiles not only during drilling but also during tripping and setting/cementing the liner. A thorough hydraulics analysis and carefully executed MPD design were used to maintain a constant bottom-hole pressure during drilling, connections, and tripping. The MPD system was fully capable of recognizing drilling parameters in real time and adjust surface pressure accordingly. This allowed the 5-7/8 in. section to be drilled using the lowest possible mud weight while attaining the necessary overbalance.
The lateral section was successfully completed to improve the stipulated timeline. This was attributable to ROP improvement by 29% and also to 164% footage drilling enhancement per bit run, which allowed the drilling team to finish the 5 7/8 in. hole section in record time compared to the offset wells. By using correct mud formulations and accurate wellbore pressure mapping, there was no loss while drilling the section; and the Early Kick Detection module was successfully deployed to accurately monitor influxes. Whenever a discrepancy was observed between the flow in/out, the MPD system was fine-tuned to adjust the pressure profile to match the two flows. Following drilling, the wash-down LWD was utilized with MPD and low mud weight. The liner was run and set, while the hole was filled with a low weight mud, using the MPD system. There were no tight spots or caving observed in the whole run and the liner was able to reach the bottom with no issues. A detailed paper would discuss the in-depth technical analysis of this case history.
A Novel Two-Stage Treatment to Remove Scales from Oil Producing Wells in a Sandstone Reservoir
Authors: Alfakher Basil M. , Al-Taq Ali A. , Alrustum Abdullah A. , Altawfiq Ali M. , AlHashim Hassan W. 
Published: June 2017

Abstract
Several oil producer wells in a sandstone reservoir have experienced productivity decline due to obstruction material. Bailer samples were collected at different depths to identify the nature of the obstruction material and recommend an optimized remedial treatment to restore productivity of damaged wells. The samples were found to be heterogeneous and contained different types of scales including calcite and iron containing compounds. Various forms of iron sulfides, iron hydroxides were present in the collected samples at different concentrations. Sand, elemental sulfur and trace amounts of iron oxides were also present in some of the samples.
Mechanisms of scales formation were investigated in this study to recommend prevention measures. As an example, greigite (Fe3S4), present as one of the major scales (49 wt. %) in one of the samples, may form due to the reaction of iron sulfide (FeS) with excess sulfur, both detected in the sample. Formation of iron sulfide was attributed to SRB's which dictates the need to have effective biocide treatments.
Solubility tests of collected scales in different dissolver systems were examined as a function of temperature and soaking time. Among other examined dissolver systems, (HCl) acid was found to be the most effective. Effects of acid additives on the solubility of scales were examined in order to optimize the acid recipe. The formation of interest is sandstone containing up to 2 wt. % authigenic clays. The use of HCl acid may induce fines migration and sanding problems. Based on lab results, a novel two-stage remedial treatment is recommended to restore productivity of damaged wells. The first stage involves treating the wellbore with HCl acid including the required additives to remove the scaling material from the wellbore area. The second stage includes incorporating organic acid to stimulate the formation matrix.
This paper presents a study detailing the design of a novel two-stage treatment able to remove scales and overcome some of the anticipated challenges in stimulation of sandstone formations. The paper also addresses results of extensive lab work conducted to optimize the treatment recipes.
CO2-Based Technologies in Unconventional Resources: Impact of Rock Mineralogy on Adsorption
Authors: Al Ismail Maytham , Zoback Mark 
Published: June 2017

Abstract
Low pressure sorption analysis and CO2 adsorption measurements were carried out on shale samples from the Utica and Permian basins. To determine the impact of rock mineralogy on the adsorbed volume of CO2, the mineral compositon of the studied samples varied. For example, the clay content of the studied samples ranged between 5% and 53%. The low pressure sorption analysis was conducted to estimate the pore-size distribution for the shale samples. Then, CO2 adsorption was measured using the volumetric method applied on an in-house experimental apparatus to generate the CO2 adsorption isotherms. The adsorption measurements were performed on crushed samples to speed up the equilibrium process. During the adsorption measurements, the temperature of the system was maintained at 40°C.
The adsorption measurements revealed that the adsorbed volume was controlled mainly by the clay content. A ~30 wt% increase in clay content resulted in an increase of the adsorbed volume by an order of magnitude. The adsorbed volume of CO2 ranged between 27 scf/ton and 152 scf/ton for the Utica shale samples and between 60 scf/ton and 640 scf/ton for the Permian samples. Based on pore-size distribution analysis, clay minerals (i.e. illite) provided the surface area for adsorption. SEM images using energy-dispersive X-rate spectroscopy (EDS) obtained for a clay-rich shale sample confirmed that the platy structure of the illite provided the surface area for increased adsorption capacity.
CO2-based technologies are emerging in the oil and gas industry for CO2 storage, stimulation and enhanced recovery. This study has shown that clay content significantly impacts how CO2 interact with the rock. Therefore, to optimally design the CO2-based technologies, rock mineralogy shouldn't be ignored.