bluuebunny/crossref_metadata_2025 huggingface dataset:
Role of Geomechanics and Integrated Reservoir Characterization in Production Enhancement from a Heterogeneous Carbonate Reservoir: A Success Story from Kuwait
Authors: Padhy Girija Shankar , Al-Rashidi Tahani , Gezeeri Taher Mohd , Shinde Ashok , Perumalla Satya , Zhou Chong
Published: March 2019

The subject upper Cretaceous carbonate formation has been characterized as a heterogeneous reservoir with varying facies and petrophysical properties. Distribution of facies strongly varied not only with depth, but also laterally across the field. Upper part of the reservoir is dominated by natural fractures whereas lower part is predominantly argillaceous with mud enrichment. In addition, presence of laminations and vugs enhanced the heterogeneity of the reservoir. Very few wells were drilled and some of them were fractured. This paper demonstrates how geomechanical and integrated reservoir characterization has shown value in well placement strategy.

Built number of well-based geomechanical models with data from all wells in order to capture reservoir heterogeneity in models. These models quantified the distribution of rock mechanical properties and pore-pressure as well as present day principle stresses. In addition, these models were integrated with geological model as well as seismic data to generate a 3D geomechanical model. After a thorough rock typing and petrophysical classification, some patterns were recognized in terms of presence of natural fractures in certain layers. However, the production contribution of these natural fractures was unclear. Upon combining all available sensitive fracture indicators, a DFN model was built and calibrated. Finally, the 3D geomechanical model combined present day in-situ stress and pore pressure magnitudes, mechanical properties of all rock facies and natural fracture occurrences at field scale. A thorough well production analysis was also performed to validate the role of natural fractures during production.

After systematic integration of diverse sub-surface data sets in 3D geomechanical model, some natural fracture subsets were identified that are optimally oriented to become critically stressed at present day stress regime. Upon further analysis, a new parameter "Index of Critically Stressed Fractures (iCSF)" was created that captured the spatial distribution of networked fracture sets in 3D model that are geomechanically favorable for fluid flow. Number of geomechanical sweetspots were identified at field scale and correlated these areas with other data. It was also recommended to stimulate wells with certain practices.

Integration of geomechanical models with production analysis and natural fracture indicators delivered value in identifying geomechanical sweetspots that have potential to flow. Distribution of these sweet spots provided a strategy for well placement as well as stimulation. In addition, this paper also exhibits logical integration of findings from geosciences and engineering disciplines to make informed decisions on well planning in order to maximize the production from challenging reservoirs.
Process Integration and Optimization of CO2 Removal from Natural Gas Using Cryogenic Distillation System
Authors: Surmi Amiza
Published: March 2019

The development of CO2 separation technologies will enable the monetization of undeveloped gas fields with a high level of CO2, thus providing commercial enterprises a superior competitive edge for future international field acquisitions. The cryogenic distillation system has been identified as one of bulk CO2 separation technologies for high CO2 removal from natural gas. It is a more favourable CO2 separation technology than chemical or physical absorption due to its independence from absorbents, which require a greater footprint, weight and energy. It is targeted for bulk CO2 removal from the natural gas stream 80% down to 20%, and it must be efficient and cost-effective to ensure that the overall economics of a development are positive.

In-house process simulation software was used to model a cryogenic distillation column system, while an experimentally validated thermodynamic model was used to verify the phase behaviour of the components, potential CO2 solidification and hydrate formation at the operating pressure and temperature conditions. This modelling encompassed critical operating conditions such as high operating pressure and low operating temperature. This is crucial especially at lower temperature and blowdown condition to prevent piping and equipment blockage which might lead to catastrophic equipment failure.

A pilot scale cryogenic distillation unit was studied in this paper with pre-mixed feed consists of CO2 and natural gas to investigate separation performance as well as to examine the operational aspects of the technology. Efforts should be made to reduce energy consumption for such applications. In this paper, pinch analysis tool is utilized to analyse and optimized the Heat Exchanger Network (HEN) of the Cryogenic Distillation System for bulk CO2 separation. Column operating pressure, condenser and reboiler temperatures and feed conditions were varied to examine the effect on energy consumptions and for comparison with process simulation results. It was found that condenser duty decreased by 50% while reboiler duty increased by 100% when operating pressure was increased from 35 bar to 50 bar to achieve the same product specification. Substantial energy reduction for external cooling was attained through pinch technology by taking advantage of the Joule-Thomson effect when expanding high pressure liquid CO2 stream to a lower pressure. Optimal operating conditions, the effect of impurities and alternative refrigeration systems are identified as current gaps in this study.

Operational issues were identified and mitigated in this study, which will further the understanding and scaling-up of commercial plants, particularly blowdown study and CO2 solid and hydrate formations and potential mitigations.
Autonomous Reservoir Nano-Agents
Authors: Mashat Afnan , Shi Nan , Squires Todd , Abdel-Fattah Amr
Published: March 2019

This article demonstrates the ability of salinity gradients that naturally exist, or could otherwise be induced, in the reservoir to target-migrate nanoparticles in porous and fractured reservoirs. This nanoparticles’ autonomous migration marks a significant milestone towards the development of reservoir nano-agents that self-migrate in deep and hard-to-reach regions in the reservoir without the aid of advective flows.

Direct microscopic visualization experiments were conducted in representative micromodel environments to quantify the displacement and velocity vectors of model nanoparticles in response to different concentration gradients of solutes in the absence of advective flow. One set of experiments used solutes with different divalent ions and another set used high-salinity water to create the concentration gradients.

Nanoparticle migration distance and speed up or down the imposed gradients were precisely obtained from high resolution image sequences using particle image velocimetry (PIV) algorithms. The rate at which the particles migrate was calculated and used to validate and extend existing theories to high salinity conditions.

Results showed that, in the absence of flow, nanoparticles readily migrate upon exposure to a given gradient, either up or down the gradient, depending on the solute composition (diffusiophoresis). The rate at which the particles migrate is on the order of μm/s and was found to be dependent on: 1) the gradient magnitude, 2) absolute value of the minimum and maximum concentration of the gradient, 3) ion diffusivities.

The results presented here provide new insights into the transport mechanisms of nano and micro particles in oil reservoirs where naturally-occurring or induced solute and chemical gradients exist. These results provide a platform for the development of reservoir nano-agents that self-migrate in deep and hard-to-reach regions in the reservoir without the aid of advective flows.
Hydraulic Fracturing in a Devonian Age Carbonate Reservoir: A Case Study
Authors: Istayev Almas , Jatykov Temirlan , Kosset Talgat
Published: March 2019

Recent technological progress within the petroleum industry has enabled much deeper discoveries than conventionally accepted depths. One example of such exploration success is drilling and stimulating an appraisal well in a Devonian age carbonate reservoir in northwestern Kazakhstan.

This paper describes a successful case study of hydraulic fracturing stimulation as a solution to enhance hydrocarbon recovery. A specific workflow developed for stimulation of high pressure and temperature low permeability reservoir is suggested. This workflow includes an adapted study of petrophysical properties, fracture geometry modeling, and completion design selection. Fracture stimulations and pre- and post-completion results are also analyzed and compared.

One of the main tasks of the technical staff was designing a production enhancement method which would maintain positive return on investment (ROI) for the project. A reservoir study was conducted during the planning stage of this pilot project. The design workflow included geomechanical analysis to estimate reservoir rock properties. Fracture stimulation modeling was performed to forecast treating pressures and adjust treatment stage sizes to help achieve optimum fracture geometries. Perforation intervals were selected and recommended to provide the best placement of fracturing fluid and proppant into the zone of interest.

Previously, the operator had attempted an acid wash, which was unsuccessful because of coiled tubing (CT) capability limitations, making it impossible to inject acid in desired rates into the rock due to low permeabilities and high stresses. Then, based on the final designed stimulation treatment plan, the operator conducted a massive proppant and acid fracturing stimulation operation, where high pressure pumping was performed at the treating pressures above formation breakdown limits. Created hydraulic fractures provided conductive pathways for reservoir fluid inflow. This method has shown an improved recovery of reservoir fluid. This hydraulic fracturing technique provided economically effective field exploration in the previously undeveloped part of the licensed block.

Field execution has shown challenges with respect to performing operations in deviated wells. Observations conducted in three stages during the pilot project are described and conclusions presented. This paper also describes operational difficulties with equipment combined with materials logistics.
FracBots: Overview and Energy Consumption Analysis
Authors: Alshehri Abdallah , Martins Carlos
Published: March 2019

Fracture Robots (FracBots) prototype has been successfully designed, developed, fabricated and tested in the laboratory. They are magnetic induction (MI)-based wireless sensor nodes that have the inter-node wireless communication, sensing and localization estimation capabilities. FracBots are miniature devices that can operate as wireless underground sensor networks (WUSNs) inside hydraulic fractures to collect and communicate important data and generate real-time mapping. The energy source of the FracBots is a major challenge since the operational environment is the hydraulic fractures which impose a restriction on the size that doesn't allow enough space for the battery. In addition, the capability to extract the energy from a designate source is another key-role feature that has to be a function of the FracBots. In this regard, energy consumption analysis and evaluation has been done to ensure that all the FracBots have the required energy to work properly during the operation inside the hydraulic fractures. The electronic design of the FracBots must be highly efficient and capable of dramatically reducing power consumption. Thus, FracBots design is composed of ultra-low power electronic chips that enable a switch among an active mode, a deep sleep mode and a shutdown mode with automatic wake-up features (Low Power Modes (LPMs). Also, it includes an energy management unit that harvests surplus power stemming from the base station. This feature reduces the power consumption and ensure continuous operation. Based on our energy model and electronic design, deep analysis of the harvested and consumed energy is conducted in a laboratory testbed. Results of this study show the capability of the FracBots to harvest the required energy to operate and perform all the communications and sensing functionalities. Using ultra-low power electronic chips based on ferromagnetic technology (FRAM) and energy management unit reduce the power consumption of the FracBots by 50% at least.
Surface Seismic with DAS Changes Land Acquisition
Authors: Bakulin Andrey , Silvestrov Ilya , Pevzner Roman
Published: March 2019

Distributed Acoustic Sensing (DAS), as a seismic sensor, has unique features allowing us to record multiple datasets with variable acquisition parameters set inside the recording box, while using one continuous recording cable and a single round of shooting. We reveal how these distinct features allow DAS to deliver multi-scale data and have the capability to focus on both the near surface and deeper targets simultaneously. We present synthetic and field examples of "deep" and "shallow" DAS surveys and demonstrate their effectiveness. The new capabilities of surface seismic with DAS technology comprise a sensing revolution that addresses long-standing near-surface issues in land seismic without compromising the deeper imaging. Achieving similar capabilities with point sensors could be done but would lead to ballooning acquisition costs, whereas surface seismic with DAS can deliver them at a cost less than conventional geophone acquisition available today.
Implementing a Drilling Reporting Data Mining Tool Using Natural Language Processing Sentiment Analysis Techniques
Authors: Kowalchuk Peter
Published: March 2019

Drilling operations generate much information, such as daily drilling reports and reports generated by service companies, support personnel, and other stakeholders. These reports can be unstructured with information presented in a variety of formats. The extraction of this information is frequently challenging, which limits its use in future projects. Natural language processing provides an efficient way of mining and obtaining knowledge. This paper demonstrates how these techniques were used to analyze vast amounts of historical documents to quickly rank well complexity and determine which aspects of drilling operations were most critical.

Sentiment analysis can be used to classify documents and other pieces of information into separate categories. In social media, it is used to analyze the collective perception of a given trending item. The technique was used here to classify wells into two ranked categorized lists. First, a classification listed wells by drilling issues. Second, a complexity ranking was defined so that each well could be classified as easy or difficult to drill. To build the sentiment analysis tool, a random set of training wells and their respective documents were selected. From these documents, a list of words was identified in what became known as highlighting sessions. During these sessions, subject matter experts (SMEs) classified words found in the documents. This "bag of words" was then used to train a classifier capable of ranking the wells related to the documents. A probability was associated to each well, providing a likelihood of inclusion in a given category.

The methodology proved to be successful, ranking drilling documents in both defined category sets. Results show that the list of ranked wells can be used by SMEs to identify which wells are relevant and deserve detailed analysis. The list generated for both categories provided a guideline for further analysis, particularly identifying wells with little value. Results also showed the importance of correctly developing a list of words, an adequate training set, and the language used, as well as the need for SMEs to produce the final analysis. The technology showed promising results with real-world applications being conceivable with its current level of maturity. However, the results also indicated room for improving its effectiveness by refining the highlighting sessions, word lists, types of classifier used, and final ranking methodology.

The use of methods and technology to help improve and enable the analysis of unstructured data in the drilling space should increase over time. This paper shows how current technology can already be used in practical real-life cases to produce tangible value.
Study on the Impact of Core Wettability and Oil Saturation on the Rheological Behavior of CO2-Foams
Authors: Beunat Virginie , Pannacci Nicolas , Batot Guillaume , Gland Nicolas , Chevallier Eloïse , Cuenca Amandine
Published: March 2019

Foam processes aim to improve the efficiency of gas-based injection methods through gases mobility control. They have been successfully applied in various EOR contexts: CCUS through CO2-EOR, steam injection for heavy oil reservoirs, and also in fractured reservoirs. The success of such processes depends on multiple factors, among which the interactions between the surfactants, the oil and the rock, play a key role. The purpose of this study is to provide initial answers by focusing on the influence of wettability and oil saturation on the behavior of CO2-foam flows.

A new coreflooding set-up is designed for ‘mesoscopic’ cores (2.5 cm diameter) in order to conduct foam formulation screening and perform faster foam injection tests at reservoir conditions (up to 200 bar and 60 °C). This set-up was first validated by repeating experiments performed previously on classical corefloods with 4 cm diameter cores. Similar results in terms of mobility reduction were obtained for the same operating conditions with a considerable reduction of test duration.

All experiments were performed with Clashach sandstones cores having approximatively 16 % porosity and 600 mD permeability. Two gas compositions have been studied: (1) a dense supercritical CO2 (density of 638 kg/m3 at P = 160 bar, T = 60°C) and (2) a non-dense gas mixture of CO2 and CH4. For each gas composition, four foam injection tests were carried out: two on water-wet rock samples, two others on crude-aged core samples, and for both in the absence and in presence of oil. Anionic surfactant formulations and gas were co-injected with a gas fraction of 0.7. Foam rheology was assessed by measuring foam apparent viscosity through a scan of interstitial velocities.

All the tests performed in dense conditions have highlighted the generation of strong foams, which present shear-thinning rheological behavior; the apparent viscosity decreases as a power law of the interstitial velocity. An influence of the wettability is observed on the foam apparent viscosity, which drops off by 30 % in altered wettability rock samples. When samples were originally saturated with oil at Swi, the level of apparent viscosity remains globally unchanged but the kinetics of the initial formation of the foam is slower with oil than without.

Foam flooding experiments are sometimes carried out simply in the presence of oil without taking into account the influence of wettability, which appears to be as important, if not more, than the oil saturation itself. These results will hopely provide some guidance for future foam studies and raise awareness on the importance of these parameters.
A Novel Approach for Optimizing Multistage Hydraulic Fracturing of Gas Condensate Horizontal Wells
Authors: Al-Garadi Karem , Aldughaither Abdulaziz , Ba alawi Mustafa , Al-Hashim Hasan , Sibaweihi Najmudeen , Said Mohamed
Published: March 2019

Condensate banking has been identified to cause significant drop in gas relative permeability and consequently reduction of the productivity of gas condensate wells. To overcome this problem, hydraulic fracturing has been used as a mean to minimize or eliminate this phenomenon. Furthermore multistage hydraulic fracturing techniques have been used to enhance the productivity of horizontal gas condensate wells especially in low permeability formation. Even though multistage hydraulic fracturing has provided an effective solution for condensate blockage to some extent as it promotes linear flow modes which will minimize the pressure drops and consequently improves the inflow performance considerably. However, this technique is very costly, and has to be optimized to get the best long-term performance of the multistage fractured horizontal gas condensate wells.

In this paper, multiple sensitivity analyses were conducted in order to come up with an optimum multistage hydraulic fracturing scenario. In these analyses, our manipulations were focused mainly on the operational parameters such as fractures half length, fractures conductivity using compositional commercial simulator. CMG-GEM simulator was used to investigate the different cases proposed for applying multistage hydraulic fracturing of horizontal gas condensate wells. The investigation began with a base case scenario where the fractures half-length were fixed for all stages with equal spacing between them. Then, six more fractures half-length patterns were created by introducing new approach where the well performance was studied if they are in increasing trend away from the wellbore (coning-up), or in a decreasing trend (coning-down). Well performance is furtherly addressed when the fractures half-length arrangements formed parabolic shapes including both occasions of concaving upward and downward. Finally, the last two patterns illustrated the effect of having the fractures half-length arrangements both skewed to the left and right on well productivity.

The investigation of the effect of changing the multistage hydraulic fractures half-length distribution patterns on the performance of a gas condensate well was conducted and resulted in parabolic up distribution pattern to be the optimum pattern amongst the other tested ones. It results in the highest cumulative both gas and condensate production. It also maintains the gas flow rate and bottom hole pressure more efficiently. The parabolic up distribution pattern confirms that the majority of gas production was fed by the fractures at the heel and at the toe of the horizontal drainhole which is in agreement with the flux distribution along the horizontal well.
Analysis of Sinusoidal Buckling of Drill String in Vertical Wells Using Finite Element Method
Authors: Cebeci Mehmet , Gücüyener ismail Hakki , Kök Mustafa Versan
Published: March 2019

The present work focuses on the stability of drill strings in vertical wellbores. The first rigorous treatment of stability of drill strings for vertical wellbores was presented by Lubinski (1950) and his equation is till most widely used in the industry. Cunha (2004) stated that since Lubinski (1950) used power series to solve differential equation governing the stability problem, and the terms of power series become very large for long drill strings, therefore, after a certain length, the calculations may lead to inaccurate results. Mitchell and Miska (2011) stated that analytical solution for infinite-length drill string is used for deep vertical wells in the industry. The subject studied in this study is of great importance in designing the bottom hole assemblies in deep and ultra-deep vertical wells to eliminate problems associated with instability of drill strings. The study includes Finite Element Method (FEM) solution of critical sinusoidal buckling force for 5 different drill collars with 21 different lengths starting from 1000 ft. up to 25000 ft. The main objectives of the study are to see the difference between post-buckling behavior of slender-dominated long hanging drill strings with stiffness-dominated short hanging drill strings in vertical wellbores; to investigate the effect of flexural rigidity of drill collars on decrease of the critical buckling forces as a length parameter of the drill string; and to see the behavior and amount of decrease in the critical buckling forces as the length of the drill string increases. And, it is showed that critical buckling force decreases as the depth of the well increases according to FEM solutions, although, analytical solution gives only a fixed critical buckling force for a specific pipe independent from the length. Also, it is showed that post-buckling behavior of slender-dominated long hanging drill strings with stiffness-dominated short hanging drill strings in vertical wellbores are different.
Phenomenology During Flowback in Unconventional Wells
Authors: Angulo Yznaga Reinaldo Jose , Quintero Luis Fernando , Negm Ehab , Van Laer Pierre
Published: March 2019

Flowback of wells after hydraulic fracturing has always been under debate because the future performance of fractured hydraulic wells depends on the operational procedure applied during the flowback. Unconventional reservoirs have become increasingly important hydrocarbon resources to develop and produce for the oil and gas industry, and the best cost-efficient approach to develop and produce unconventional reservoirs is by drilling and completion of horizontal multi-stage hydraulic fractured wells. Hence the complexity of the phenomenology seen during the flowback of this type of wells has increased substantially. The complexity of the phenomenology is the result of the change on the range of fluid and fluid-rock properties. The permeability of unconventional reservoirs is typically in the range of nano to low micro darcies. This implies that the forces acting on the fluid flow through the medium are extremely magnified. This paper is aimed at describing the phenomenology during early fluid flow in unconventional wells, and its relevance during the design, planning, and execution of well flowback.

The work considers actual data and information of flowback in unconventional wells from the available literature, as well as our own experiences. The authors use this available data and information to describe the physical phenomena that occurs in unconventional wells, especially in the early stages of production testing. The paper describes a theoretical approach that explains the fluid behaviour seen during multi-stage hydraulic fractured unconventional wells. Finally, the flowback is characterized based on the phenomenology, and its description provides an approach to an improved design of well flow management.

The characterization of the phenomenology during flowback allows us to identify six stages of fluid flow in unconventional wells during the early flow process. Each stage has been identified considering the acting forces, fluid flow, and implications during the flowback. After such description, flowback design is explained based on the phenomenology characterization. Finally, the authors provide a comparison of the design and the actual behaviour for the early stages of flowback.

This work introduces an approach based on the characterization of the phenomenology associated to multi-stage hydraulic fractured unconventional wells that have been successfully applied in flowback operations. A comparison between theoretical designs and actual cases confirms the value of the methodology.
Advanced Eor Foam in Naturally Fractured Carbonates Reservoirs : Optimal Balance Between Foam and Interfacial Tension Properties
Authors: Chevallier Eloïse , Bouquet Sarah , Gland Nicolas , Douarche Frédéric , Batôt Guillaume
Published: March 2019

In naturally fractured carbonate reservoirs, Gas Oil Gravity Drainage processes (GOGD) are successfully implemented but oil recovery is limited by a slow kinetics. However a gas EOR process represents a promising alternative to boost this oil production rate. Nevertheless the design of this process should address several technical challenges: the typically unfavorable wettability of the matrix (intermediate to strongly oil-wet), the densely connected fracture network and the high contrast of fracture-to-matrix permeability.

We propose here the injection of a advanced EOR foam with reduced interfacial tension. The foam flow in the fracture creates an important viscous drive leading to a pressure gradient, which increases the oil recovery dynamics compared to GOGD. Besides, the reduced interfacial tension (IFT) between crude oil and aqueous phase allows the aqueous phase to enter the matrix despite the unfavorable wettability.

In this paper, we demonstrate that a balance exist between IFT and foam strength performances to optimize the process. Three foam formulations are optimized with very different profiles in terms of IFT and foam performances. For their design, priority is given either to ultra-low IFT values (10-3mN/m) or to a strong foam with larger IFT (0.35mN/m) or to a balance between the two first formulations (0.03mN/m). Foams are evidenced as intrinsically less stable in ultra-low IFT conditions: apparent viscosity (in porous media) in contact with oil is respectively enhanced by a factor 40 when IFT rises from 10−3 to 10−1mN/m. Based on sandpack and coreflood experiments, we recommend an IFT in the order of 10−1 mN/mas a balance between the viscous drive in fracture and an efficient aqueous phase imbibition in the oil-wet matrix. Simulation work supports this experimental conclusion: the common target of IFT in the order of 10−3 mN/m determined by capillary desaturation curves in SP flooding can be adjusted to a higher IFT value, which can be deduced from the wettability of the reservoir.

To ensure an accelerated oil recovery in naturally fractured carbonate reservoirs, we recommend the design of a low-IFT foam formulation with revised IFT performances compared to a classical Surfactant-Polymer process targeting residual oil. Indeed, the final process is likely more efficient if the target of IFT is defined by wettability requirements rather than residual oil desaturation. This article gives the target formulation parameters which arise from the mechanisms at play (viscous drive and imbibition in oil-wet matrix), and are realistically achieved with industrial surfactants.
First Rigless Water Shutoff and Reservoir Cross-Flow Leak Mitigation Performed in the United Arab Emirates on a Horizontal Extended Reach Well, Enabling Improved Reservoir Management
Authors: Wills Andrew , Wheatley Jason , Sau Rajes , Jimenez Jose , Ulloa Joel
Published: March 2019

The latest developments in well construction rely on advanced drilling and completion technologies to withstand increased wellbore deviation, tortuosity, and complex geometry challenges necessary to access reservoirs, which can create challenges to cement placement between reservoir zones. Hence, well integrity and reservoir management concerns can arise given the possibility for multiple reservoirs to communicate, resulting in undesired crossflow and water production because of poor cement isolation.

Poor cement placement behind casings, ineffective zonal isolation, and well integrity issues have been traditionally addressed using workover or drilling rigs to remove production tubing and perform either a remedial cement squeeze or zonal abandonment for subsequent sidetrack. However, this generally entails production deferral, capital-intensive rig rates, the potential risks of pulling and running production tubing, which often translates in formation damage from killing the well, large wellsite footprint requirements, and higher logistic demands for rig support equipment.

This paper describes the systematic process used to identify, diagnose, design, and execute a successful inter-reservoir crossflow mitigation operation in a naturally fractured carbonate formation in Abu Dhabi using a cost-effective solution with rigless coiled tubing-deployed technologies and a hydrocarbon-based microfine cement slurry that activates upon contact with water. The results enabled the operator to restore reservoir integrity, improve reservoir management, and enhance water sweep.

Post-operation reservoir evaluation validated the successful use of the technology for rigless zonal isolation using coiled tubing (CT) for the first time in the United Arab Emirates, providing significant cost benefits and new best practices to reduce the water cut and restore wellbore integrity.
When Petrophysics Meets Big Data: What can Machine Do?
Authors: Xu Chicheng , Misra Siddharth , Srinivasan Poorna , Ma Shouxiang
Published: March 2019

Petrophysics is a pivotal discipline that bridges engineering and geosciences for reservoir characterization and development. New sensor technologies have enabled real-time streaming of large-volume, multi-scale, and high-dimensional petrophysical data into our databases. Petrophysical data types are extremely diverse, and include numeric curves, arrays, waveforms, images, maps, 3-D volumes, and texts. All data can be indexed with depth (continuous or discrete) or time. Petrophysical data exhibits all the "7V" characteristics of big data, i.e., volume, velocity, variety, variability, veracity, visualization, and value. This paper will give an overview of both theories and applications of machine learning methods as applicable to petrophysical big data analysis.

Recent publications indicate that petrophysical data-driven analytics (PDDA) has been emerging as an active sub-discipline of petrophysics. Field examples from the petrophysics literature will be used to illustrate the advantages of machine learning in the following technical areas: (1) Geological facies classification or petrophysical rock typing; (2) Seismic rock properties or rock physics modeling; (3) Petrophysical/geochemical/geomechanical properties prediction; (3) Fast physical modeling of logging tools; (4) Well and reservoir surveillance; (6) Automated data quality control; (7) Pseudo data generation; and (8) Logging or coring operation guidance.

The paper will also review the major challenges that need to be overcome before the potentially game-changing value of machine learning for petrophysics discipline can be realized. First, a robust theoretical foundation to support the application of machine leaning to petrophysical interpretation should be established; second, the utility of existing machine learning algorithms must be evaluated and tested in different petrophysical tasks with different data scenarios; third, procedures to control the quality of data used in machine leaning algorithms need to be implemented and the associated uncertainties need to be appropriately addressed. The paper will outlook the future opportunities of enabling advanced data analytics to solve challenging oilfield problems in the era of the 4th industrial revolution (IR4.0).
Applications of Artificial Neural Networks in the Petroleum Industry: A Review
Authors: Alkinani Husam H. , Al-Hameedi Abo Taleb , Dunn-Norman Shari , Flori Ralph E. , Alsaba Mortadha T. , Amer Ahmed S.
Published: March 2019

Oil/gas exploration, drilling, production, and reservoir management are challenging these days since most oil and gas conventional sources are already discovered and have been producing for many years. That is why petroleum engineers are trying to use advanced tools such as artificial neural networks (ANNs) to help to make the decision to reduce non-productive time and cost.

A good number of papers about the applications of ANNs in the petroleum literature were reviewed and summarized in tables. The applications were classified into four groups; applications of ANNs in explorations, drilling, production, and reservoir engineering. A good number of applications in the literature of petroleum engineering were tabulated. Also, a formalized methodology to apply the ANNs for any petroleum application was presented and accomplished by a flowchart that can serve as a practical reference to apply the ANNs for any petroleum application. The method was broken down into steps that can be followed easily. The availability of huge data sets in the petroleum industry gives the opportunity to use these data to make better decisions and predict future outcomes. This paper will provide a review of applications of ANNs in petroleum engineering as well as a clear methodology on how to apply the ANNs for any petroleum application.
Automated Artificial Intelligent Pressure Gradient Analysis for Fluid Contact and Compartmentalization Analysis
Authors: Stark Daniel , Jones Christopher , Dai Bin , van Zuilekom Anthony
Published: March 2019

The reservoir compartmentalization structure and fluid contacts of a field are essential for determining the value of a reservoir asset and provide the two primary purposes of pressure gradient determination. Several new straightforward data-analytical methods have been developed to extract pressure gradient information based on physical properties of the reservoir and meta-analysis of derived pressure gradient information. These methods can be used to provide near real-time feedback about the pressure measurements quality.

This paper describes two distinct methods to determine reservoir compartmentalization structure and fluid contacts. The first method implements statistical evolution to rapidly identify pressure gradients. The second method transforms identified pressure measurements into a meta-analytical visual representation of pressure gradients vs. depth with additional input from measurement consistency. Both methods rely on the accurate removal of pressure outlier data, such as that attributable to supercharging. A new technique using expert knowledge of physical constraints was implemented for reliable outlier removal. The two methods then diverge in subsequent conditioning of the data, but re-converge in adapting an efficient fitting method to extract the desired information.

Both methods provide reliable removal of pressure data that are not related to formation fluid densities, regardless of reservoir number, fluid number, or fluid type. To date, the removal procedure removes more than 95% of outliers and retains more than 90% of accurate pressure data. Both methods also return the correct number and types of fluids. Although pressure gradient estimation can vary by up to 50% for fluid zones of less than 50 ft, the estimation error of the pressure gradients is reduced to less than 3% for fluid zones greater than 100 ft. Furthermore, fluid breaks can be calculated to within 8 ft for the statistical evolution method and to within 30 ft using the visual method. Finally, although the statistical evolution method is markedly faster than the visual method, both techniques provide feedback within a few minutes.

The methods discussed provide feedback about the necessity to retake or take more pressure data during formation-pressure surveys within minutes. This feedback eliminates the delay in reservoir property estimation and greatly increases the reliability and quality of pressure data obtained. The methods presented also use a new application of data meta-analysis to reduce processing time and increase reliability.
A New Decline Curve Analysis Method for Layered Reservoirs
Authors: Jongkittinarukorn Kittiphong , Last Nick , Escobar Freddy , Maneeintr Kreangkrai
Published: March 2019

This study presents a new method to improve production forecasts and reserves estimation for a multilayer well in the early stages of production, using Arps’ hyperbolic decline method to model the decline rate of each layer. The method can be applied to both oil and gas wells.

The new approach generates the profiles of instantaneous decline rate (D) and instantaneous decline exponent (b) from the historical flow rate (q). Because of the inherent noise in the production data, a regression technique is applied to smooth the flow rate data and the analysis is performed on the smoothed data. History matching is performed not only on the profile of q, but also on the profiles of D and b. The results are the unique decline parameters (qi, Di, and b) for each layer.

For a multi-layer well, the values of D and b vary with time, which means that its performance cannot be modeled using a conventional single-layer well approach. Furthermore, the well-known non-uniqueness problem from history matching is magnified in a multilayer well: many models can successfully match the production profile in the short term but fail to match it in the longer term. Only the correct model can match the profiles of q, D, and b over both the short-term and the long-term. The proposed method provides the correct unique decline parameters (qi, Di, and b) for each layer, during the early stage of production, and these parameters are then valid for the life of the well. The method works well for both synthetic examples and actual field data.

The novelty of the new methodology is the ability to provide the decline parameters for each layer at an early stage of production, which can then be used for production forecasting in the long term. The non-uniqueness problem from history matching is solved.
Opeimizing Operation Oversight of Bahrain Field through Aerial Survey
Authors: Nooraldeen Yasser , AlNoaimi Hasan
Published: March 2019

The Bahrain Oil Field is located in a desert environment in the south-central area of the Kingdom of Bahrain and spans approximately 25% of the island. The Bahrain Field was discovered in the early 1930s and is recognized as the first oil field developed in the Arabian Gulf.

Recently, Tatweer Petroleum introduced advanced Unmanned Aerial Vehicles (UAV), also known as (Drones), to address the unique needs of its daily operation by providing a safe, efficient, and cost-effective maintenance and inspection solutions.

This paper demonstrates the valuable benefits of utilizing UAV (Drones) in the oil and gas industry in three main areas: ‘Security, Surveillance, and Emergency Response,’ ‘Inspection and Maintenance,’ and ‘Surveying and Mapping.’

Under the Security and Surveillance front, Tatweer Petroleum is facing operational safety issues and security threats that require real-time response solutions, and the need to provide rapid, precise, and reliable situational awareness. Tatweer’s Drones support the Security team with dynamic perimeter surveillance, intruder alerts, and critical equipment and process monitoring. Additionally, the Drones are used to support the emergency response team as a professional tool for rapid aerial incident investigation, evacuation, monitoring, and remote hazard detection.

Preventive maintenance inspection is another application area where Drones can play a vital role. This is especially true when it comes to inaccessible operational assets due to their physical location (e.g. overhead power lines insulators), sheer magnitude (e.g. solar cell farm), or an inherent process hazard (e.g. flare stacks). Airborne cameras with advanced spectral imaging technology and powerful magnification optics can capture, analyze, and identify particular anomalies such as oil or gas leaks and pre-failure overheats, and provide vivid close-up images of fatigued structures and micro failures in plants and assets. This is a great cost-effective and efficient method for inspection and failure prevention.

Surveying and mapping an industrial environment is time-consuming, difficult, and often dangerous. Tatweer Petroleum used the Drones to allow surveyors and mappers to collect unlimited aerial data with precise measurements, while saving time, money, and manpower. It also provides premium processing and analytics capabilities to support critical processes such as stock pile volume measurements, terrain mapping, site planning etc. The Drones are preprogrammed to automatically cover any particular area in the Bahrain Field. The survey data produces highly accurate, best-in-class orthophotos and digital elevation models.
Using Supervised Machine Learning Algorithms to Predict BHA Walk Tendencies
Authors: Noshi C. I. , Schubert J. J.
Published: March 2019

Directional drillers have faced numerous challenges due to the right and left BHA walk tendencies. Walk, build, and drop tendencies increase sliding time thus reducing ROP and increasing CPF. Drilling tortuous wellbores are more prone to NPT, increased torque and downhole drag. It was noted that bit side forces and the tilt angle influence the DLS of the wellbore. In this study, novel predictive analytic models were developed to understand the factors that influence BHA assembly walk tendency as well as uncover the hidden relationships between several different features influencing the walk tendencies. Sixty-eight wells are included in this study with an initial model training and testing being executed on eight wells. A blind test was later performed on 57 wells with 149 different BHAs. The model accounted for the number and locations of the various components in the BHA and their different types. The modified BHAs are assumed to be a continuous beam supported by PDC bits, PDM, stabilizers, and an assembly, mirroring the contact points of the BHAs, and the wellbore. For simplification purposes, the assembly assumes that all three components are made of non-magnetic material with comparable OD, linear weight, and material. The assembly was based on the fact that these components had the same bending stiffness due to similar material and thus elasticity.

Seven different ML models were experimented with to determine the lowest MAE. They included Gradient Boosting Machine, Random Forest, Artificial Neural Networks, and Adaboost. The attributes included mud density and formation type. Bit variables were composed of: OD, gauge length, length of inner and outer profile, TFA, manufacture, cutter size, and blade count. For PDM: location, OD, LW, length, bit to bend distance, and bend angle. The stabilizer included location, blade count, gauge length, gauge OD, LW, and stabilizer to bit depth and assembly specifications. Moreover, hole size, block height, hookload, WOB, ROP, differential pressure, mud flow rate, SPP, GR, Annular pressure loss, MSE, ECD at Bit, Bit RPM, Bit TOR, and bit aggressivity. The survey data had MD, Inclination, azimuth, and finally DLS.

The models showed that the side forces in the form of seven dominant factors were the main culprits in influencing the walk direction of the drill bit. There was a highly significant relationship with a MAE of 14.7% between stabilizer location, gauge OD, PDM bit to bend distance, bit gauge, PDM differential pressure, ROP, WOB, inclination, and Hookload.

These results prove to be a great advantage in controlling the drilling direction and reaching the target zone in minimal time. The optimized machine learning model helped optimize rotatory drilling time, ROP, smoother wellbores, and Lower CPF overall.