bluuebunny/crossref_metadata_2025 huggingface dataset:
Asphaltene Deposition in Metal Pipes: Efficient Inhibition and Removal by Different Surfactants
Authors: Hashmi Sara M. , Firoozabadi Abbas
Published: September 2013

We describe asphaltene deposition and removal processes in metal pipelines. We induce asphaltene precipitation by adding an asphaltene precipitant, heptane, to a petroleum fluid. The mixture is then injected through a lab-scale pipeline and allowed to deposit. We assess the inhibition or reversal of the deposition via the use of three separate chemical treatments: 1) a non-ionic dispersant, 2) a strong organic acid dispersant, and 3) an aromatic solvent. We find that the non-ionic dispersant under consideration (BA), has the ability to reduce the amount of precipitated asphaltenes when co-injected with the petroleum fluid-heptane mixture. Our previous studies show that, even at 10 ppm, BA can stabilize dilute colloidal suspensions of asphaltenes, but even high concentrations cannot dissolve asphaltenes. For this reason we investigate BA as a potential asphaltene deposition inhibitor. The strong organic acid surfactant, dodecyl benzene sulfonic acid (DBSA), has been shown to completely dissolve asphaltenes via acid-base chemistry reactions at heteroatomic sites on the asphaltene molecules. We investigate the use of DBSA as an efficient removal agent, injecting it in a mixture of petroleum fluid after the deposit has already been formed. An aromatic solvent, toluene, is also investigated in such a fashion, to assess its ability in removing deposited asphaltenes. We find that DBSA can effectively remove asphaltene deposits quickly and at concentrations roughly ten times less than that required by toluene. To the best of our knowledge, our current study is the first lab-scale investigation using dispersant or surfactant chemicals to either inhibit or reverse asphaltene deposition in pipes.
Aspects of Oilfield related Accidents
Authors: Qi Qianru , Ershaghi Iraj
Published: September 2013

Petroleum engineering literature contains limited reviews or documentations of oilfield accidents. We considered a number of cases which in the past have resulted in human fatalities, injuries and environmental disasters. Our study included a number of oilfield accidents ranging from drilling operation to pipeline transportation. Publicly available analysis of these case studies indicates accidental causes ranging from mechanical malfunctioning, electric shocks, falling objects, human errors and management flaws. For the studies included in our analysis, however, we observe that unless we resort to innovating and install advanced techniques for early failure prediction and monitoring for protecting workers, other similar events can re-happen with unfortunate impact on safety of human and the environment. As such, steps must be taken to not just enacting system integrity monitoring but also developing tools for empowering and enhancing human senses or system sensors for predicting failures and thus saving lives. This becomes particularly more critical in work processes where either overwhelming volume of incoming signals or, on the opposite, lack of critical sensor data become matters of concerns. Our review also show that critical situations develop when human response time is out of sync with unexpected systems responses and, more importantly, when human attitude about risk and safety, contributes to the disasters.

Lessons learned show that, while it is important to equip oilfield workers with the appropriate attire, safety tools and decision making systems, it is more important to support workers with remote monitoring and early warning systems. This will help for real time sensing and failure prediction of systems integrity for safeguarding oilfield workers when they deal with complex systems and/or when they may need to make decisions under duress. These remote monitoring systems must be able to rapidly process information from multitudes of sensors and sensor nets and provide real time feedback to the workers for protecting them against their shortcomings in their sensing limitations and for potential human related attitudes that can cause accidents.
Petroleum Engineering Curricula: Is it Better to Enhance Geographical Diversity or to Standardize International Education?
Authors: Falcone G. , Teodoriu C. , Barrufet M.
Published: September 2013

While it is commonly accepted that a job in petroleum engineering (PE) typically involves international traveling and assignments abroad, PE curricula around the globe still tend to reflect country-specific traditions and the needs of the local oil and gas industry.

Historically, oil and gas schools had a focus on local market needs, but more recently, several US and UK institutions have opened campuses in the Middle East, which mirror their original curricula at home. These initiatives were a response to local needs for qualified PEs to international standards.

Today, PE programs compete nationally and internationally to recruit top students and deliver top graduates. Inevitably, this makes one wonder whether the oil and gas industry would benefit from a standardized, international PE curriculum. For example, the SPE has already put significant effort into the harmonization of PE studies.

The paper sets out what the industry believes it wants from its PE graduates regarding their skills and behaviors. Then, based on the authors' own experience of selected PE curricula from USA and Europe and, by focusing on the Master of Science (MS) level, it compares the relative benefits of having a 1-year or 2-year MS program. It asks whether these programs should produce rounded PE graduates or specialized practitioners in given sub-disciplines. Finally, the paper discusses whether the industry would benefit more from a standardized, international PE curriculum or from region-specific programs, reflecting the traditional expertise and local technical priorities.
Identifying Small Leaks with Ultrasonic Leak Detection-Lessons Learned in Alaska
Authors: Julian J. Y. , Duerr A. D. , Jackson J. C. , Johns J. E.
Published: September 2013

Detection of very small tubing leaks (less than one gpm) is difficult using conventional logging techniques such as spinners and temperature logs. Leak identification is an even greater challenge for leaks behind tubing. Ultrasonic leak detection was introduced in 2005 to Alaska, and 260 logs have been run to date with an 88% success rate. Leak identification has been accomplished in wellheads, tubing, tubing connections, jewelry, gas lift mandrels, packers and production casing.

Development of this tool to be conveyed on memory with wireline and coiled tubing has resulted in cost savings due to rig up efficiencies. It has also led to additional opportunities for logging higher pressure wells in which it is difficult to maintain a pressure seal with electric line.

The ultrasonic logging tool incorporates data acquisition equipment and filtering algorithms which allow continuous logging, filtering out the "road noise" of the tool as it travels up and down the wellbore. This advantage makes it far superior to old-style noise logs which require time consuming stationary counts. Ultrasound energy attenuates very rapidly, but has the ability to transmit through tubulars, wellbore fluids, and cement. These two attributes allow pinpoint accuracy for leaks as small as 0.005 gallons per minute (gpm) even behind multiple strings of tubulars. The advantage of finding small leaks is that once the leak is identified, the well can often be remediated without the use of a rig at a fraction of the cost.

Application of this tool has great significance for any operator concerned with well integrity, and particularly, in areas where rig workovers are expensive, including remote, offshore, and arctic locations. This paper discusses the history and success rate of jobs performed to date in Alaska. It provides success statistics for both real-time and memory mode, and details non-rig remediation success and lessons learned in field operations.
Applying Calibration to Improve Uncertainty Assessment
Authors: Fondren Mark E. , McVay Duane A. , Gonzalez Raul A.
Published: September 2013

The oil and gas industry is full of uncertainty. In addition to significant subsurface uncertainty and uncertainty in oil and gas prices, there are other risks, e.g., political, that contribute to uncertainty in oil and gas projects. Capen (1976) demonstrated that industry routinely underestimates uncertainty, often significantly. The cost associated with underestimating uncertainty, or overconfidence, can be substantial. According to McVay and Dossary (2012), moderate overconfidence and optimism can result in expected portfolio disappointment of more than 30%. While McVay and Dossary assessed the cost of underestimating uncertainty, they did not fully address how to better assess uncertainty. Capen and other authors have suggested that uncertainty can be best assessed through look-backs and calibration, i.e., comparing actual results to probabilistic predictions over time. While many recognize the importance of look-backs, calibration of probabilistic estimates does not appear to be commonly practiced in the industry. Part of the reason for this is lack of systematic processes and software for calibration.

We developed a relational database application to track probabilistic estimates and assess their reliability over time. The Brier score and its components, mainly calibration, are used for assessing reliability. The system is general in the types of estimates and forecasts that it can monitor, such as production, reserves, times, costs, and quarterly earnings. Probabilistic forecasts may be assessed visually, using calibration charts, and quantitatively, using calibration and Brier scores. The calibration information can be used to modify probabilistic estimation and forecasting processes as needed to be more reliable. Calibration results from historical forecasts may be used to externally adjust future forecasts so they are better calibrated. Three experiments with historical data sets of predicted vs. actual quantities are presented to demonstrate that use of probabilistic forecast calibration results improves future forecasts. Consistent application of this approach and database application over time should improve probabilistic forecasts, resulting in improved company and industry performance.
Calculation of Erosional Velocity Due to Liquid Droplets with Application to Oil and Gas Industry Production
Authors: Arabnejad H. , Shirazi S. A. , McLaury B. S. , Shadley J. R.
Published: September 2013

The American Petroleum Institute Recommended Practice 14E (API RP 14E) describes a method for calculating an "erosional" velocity, a threshold velocity at which it is presumably safe to operate. The origin of this guideline appears to remain a mystery, but some authors and operators assume that the basis for API RP 14E is erosion due to liquid droplet impacts. However, there is no experimental evidence supporting this idea. In this work, a method has been developed to calculate erosion resulting from liquid impact for pipeline materials that are used in oil and gas industry applications. Material loss data has been collected for several oil field materials such as stainless and carbon steels, chromium alloys, inconel and duplex utilizing specimens that were mounted on a rotating flywheel and impacting liquid jets. The data and American Society for Testing and Materials (ASTM) G73 guideline are combined to develop a method for calculating erosion resulting from liquid droplets impacting the surface of the pipe materials under specific flow conditions. The results from this model have been compared to data provided in the literature for both liquid jets and droplets impacting specimens utilizing different materials, droplet sizes or jet diameters and velocities. Although the model was developed based on data at relatively low velocity conditions, the results agree well with data for a variety of flow speeds and conditions. Furthermore, the model for liquid impact erosion is used to predict threshold velocities for specific flow conditions for elbow geometry to avoid erosion-corrosion due to liquid impacts. Moreover, the results of this model are compared for several different flow conditions with API RP 14E. It is shown that the trend of the erosional velocity calculated by the API guideline does not correlate with the erosional velocity calculated by the present method that is based on the liquid droplet erosion model.

The model presented in this work will be improved as more data and information becomes available. An example is provided in which Computational Fluid Dynamics simulations are being used for different droplet and impinging jet diameters to improve the performance of the model.
Challenges and Opportunities of LWD Sampling: A Case Study from the Gulf of Mexico
Authors: Cartellieri A. , Pragt J. , Galvan-Sanchez F. , Meister M.
Published: September 2013

This paper presents the capabilities and operation of a logging-while-drilling (LWD) fluid analysis and sampling tool in a deep-water application in the Gulf of Mexico. The operation was performed during a drilling run in a high-pressure/high-temperature (HPHT) well with an expected downhole pressure of up to 22,000 psi and 300°F downhole temperature. This paper will show how a robust fluid analysis and sampling campaign was planned and executed, matching the various objectives and technical requirements with the appropriate technology. The challenges and opportunities of LWD sampling will be discussed, especially under tough environmental conditions.

The advantages of LWD sampling systems are well known, such as shorter pump-out time due to less invasion and the ability to capture reservoir fluid samples in extended reach drilling or highly deviated wells, which provides a new application range compared to current wireline systems. As the harsh drilling environment generates severe shocks and vibration, it requires precaution in the tool design and the selection of suitable components. The influence of the downhole dynamics on the reliability and durability of the system needs to be considered.

In response to these challenges, the new LWD tool incorporates an electro-mechanical driven drawdown pump that further improves the LWD fluid analysis and sampling service. This enables a nearly autonomous operation with the assurance that fluid phase integrity is being maintained. Automation allows optimal use of the available bandwidth to deliver the most complete set of fluid property data in real time for efficient decision making, including density, viscosity, sound speed and refractive index. It enables the operator to monitor the fluid identification (fluid ID) trend carefully and in real time, even from remote locations.

The sampling process is performed shortly after the hole is drilled and is therefore subjected to different levels of invasion and contamination arising from the effects of the drilling fluid and the reservoir properties. It will be discussed how this effects the clean-up and the ultimately achievable contamination level. The newly introduced compressibility value derived from the electro-mechanical pump offers a bulk measurement, where localized sensors observe scattered data. Examples from the application in the Gulf of Mexico (GOM) will be shown and discussed.

An outlook will be given how this technology evolves in future developments and how the operator and oil company can benefit from the new technologies in the drilling environment.
Closed Loop Automation of Downhole Weight on Bit Improves Sliding Performance and Reduces Conservatism in Unconventional Horizontal Well Development
Authors: Pink Tony , Koederitz William , Barrie Alex , Bert Dave , Overgaard Darrel
Published: September 2013

Today, during the development of unconventionals, the lack of knowledge of the downhole dynamics environment creates a culture of conservatism where excessive safety margins need to be applied to prevent damage to the rig equipment, drill bits, drill string and sensitive drilling tools. By using downhole data in real time, this risk can be reduced and drilling performance can be significantly improved.

This paper discusses the results of the latest field test program of an automated drilling system where direct closed loop control of machines performs drilling optimization tasks using high speed downhole data. The downhole data is measured by a downhole drilling dynamics sub and is then transmitted to the surface via wired drill pipe. The downhole data is visualized and analyzed by a surface application. The surface application then sends set points through a control interface to the rig's pre-existing control system.

The paper focuses on two main areas. The first is the rate of penetration improvements that occurred, while rotating, sliding, and sliding using an automated rocking application (Maidla and Haci 2004) and secondly, the positive behavioral change that occurs when the downhole environment is fully understood.

These technologies bring significant benefit to our industry especially in the development of unconventional assets where sliding becomes slow and more challenging the longer the horizontal. The results demonstrated that these technologies significantly improve sliding performance up to 100%, especially when combined with a surface top drive rocking technology. The high speed downhole drilling dynamics data allowed the driller and the customer representatives to maximize the performance of the rig without compromising safety or the reliability of the equipment.
Unconventional Completions: Which one is Right for Your Application?
Authors: Burton W. Aaron
Published: September 2013

In the last five years North America has changed the oil and gas markets by using horizontal drilling and multistage hydraulic fracturing to unlock the hydrocarbons in low-permeability reservoirs. This unexpected increase in natural gas production over a short period of time in the US has led to extremely low prices due to over-supplying the market. There are indications that the US will become an exporter of natural gas, rather than an importer, as originally planned. These plays require new technologies that enable reservoir characterization, horizontal drilling, multistage completions, and multistage hydraulic fracturing. All these technologies have evolved at a very rapid pace and continue to do so. This paper will focus on the completion technologies.

Three completion techniques have emerged as the most effective and efficient in these types of formations; plug-and-perf, ball-activated completions, and coiled tubing-activated completions. The plug-and-perf technique is cemented in place and uses composite bridge plugs and perforations to isolate and divert the fracture to the correct stage. Ball-activated completions use openhole packers to isolate the annulus and ball-activated fracture (frac) sleeves to divert the fracture to the intended stage. Coiled tubing-activated completions use cement to isolate the annulus, and coiled tubing-activated sleeves or perforations to divert the frac fluid.

Each completion technique has benefits and considerations. The primary purpose of this paper is to give an overview of these completion types, discuss the benefits and considerations, and how they compare in different applications from an operations point of view. The secondary purpose of this paper is to discuss how drilling, completion, and fracturing can greatly affect each other and create limitations if these processes do not collaborate.
Fluid Hammer Increases PDC Performance through Axial and Torsional Energy at the Bit
Authors: Powell Scott , Herrington David , Botton Benoit , Ivie Brad
Published: September 2013

Increasing drilling efficiency and performance are key factors for determining whether or not a new play is viable for drilling. Although several factors affect drilling cost, one key element in reducing cost is reducing drilling time by increasing the rate of penetration. This is accomplished by changing the way a drill bit interacts with the formation and analyzing different ways to overcome the factors that limit drilling performance.

New performance drilling tool designs are brining conventional mud motors into the next generation with performance driven technology. This technology features the latest generation of performance elastomers with a new energy distribution system which enhances the rock failing properties of the attached bit. This is achieved by applying both axial and torsional loading to the bit at the same time.

Conventional motors are limited by torsional loading which correlates to the differential pressure a power section can hold before it stalls. The interaction between the bit and the rock correlates to this stall pressure of the power section used. The new performance technology takes this torsional load and merges it with the axial load created by the weight of the drill string, which it then oscillates axially. The combination of axial and torsional oscillating movement amplifies the cutting interaction of the bit to help overcome the compressive strength of the formation being drilled.

Due to the unique design and different available configurations, this technology is compatible with both roller cone and fixed cutter bit designs. This design allows for constant contact between the bit and formation, reducing any bit bounce or stick slip which could reduce drilling efficiency. Along with increasing bit performance it also helps reduce weight stacking by reducing friction caused from interaction between the BHA and formation. This has proven to help with weight transfer to the bit and to reduce motor stalling, thereby improving directional control.
Remote Gas Detection System Using Infrared Camera Technology and Sophisticated Gas Plume Detection Computer Algorithm
Authors: Abdel-Moati H. M. , Morris J. M. , Ruan Y. , Zeng Y.
Published: September 2013

ExxonMobil Research Qatar and Providence Photonics, LLC, a U.S. based firm, are undertaking research to develop a Remote Gas Detection (RGD) system that integrates computer vision algorithms and infrared (IR) optical gas imaging technology to achieve autonomous remote detection of hydrocarbon plumes. The RGD system is designed to provide continuous surveillance and early warning to operations personnel in case of gas releases and to detect fugitive gas emissions.

The RGD system utilizes a custom built IR imager and integrated cooler assembly, and a computer vision algorithm that analyzes the video output from the IR imager to determine the presence of hydrocarbon plumes. Most hydrocarbons have strong absorption peaks in a narrow mid-wave IR (MWIR) region. The algorithm takes advantage of the difference in contrast between a hydrocarbon plume and the background in an IR image and the temporal changes due to plume behavior for the analysis. The algorithm compares sequentially collected IR images and uses a multi-stage confirmation process to confirm the detection. It has multiple filters that mitigate interferences like steam and other movement of objects in the scene such as humans, vehicles, and trees. Early field tests indicate that a 4 lb/hr propane leak could be autonomously detected from a distance of up to 800 feet.

The RGD camera assembly enclosure is designed to obtained explosion proof certification using the ATEX standard for deployment at classified/hazardous areas in oil and gas processing facilities. Instrument air provides cooling and is used to purge the system. Multiple deployment opportunities at process facilities are currently underway. Results from field testing at these process facilities will help researchers investigate the effect of temperate and harsh weather conditions, the effect of varying temperatures and gain a better understanding of equipment wear and tear, maintenance requirements and life expectancies. These data sets will produce an accurate assessment of the performance of the RGD system under actual working conditions and will be used to qualify the technology for widespread adoption within the industry.

Work has also been undertaken to compare the performance of the RGD system versus existing detection technologies. The most common leak detection technology is point sensors and path infrared sensors. This technology requires dispersed gas to physically contact the point sensors or move between two path detectors. Field tests are used to compare the performance of these mature technologies to the capabilities of RGD.
Interpreting Pressure and Flow Rate Data from Permanent Downhole Gauges with Convolution-Kernel-Based Data Mining Approaches
Authors: Liu Yang , Horne Roland N.
Published: September 2013

The paper describes a method of analyzing data from permanent downhole gauges, even in the presence of noise, gaps and outliers. The data mining approach developed allows for the revelation of the underlying data signal, and as a useful corollary also achieves deconvolution to compute the reservoir model – even with the existence of significant noise in the data.

The convolution kernel was initially invented and applied in the domain of natural language machine learning. In the original linguistic study, the convolution kernel detected the relationship between words by decomposing words into parts, and evaluating the parts using a simple kernel function. The success of the convolution kernel method inspired us to apply it to data from permanent downhole gauges (PDG). In this study, the data mining process was conducted in two stages, namely learning and prediction processes. In the learning process, the PDG data that were decomposed into a series of pressure responses to the previous flow rate change events were used to train the convolution-kernel-based data mining algorithm until the convergence. After convergence, the reservoir model was obtained implicitly in the form of polynomials in the high-dimensional Hilbert space defined by the convolution kernel function. In the prediction process, a pressure prediction was made by the reservoir model (obtained in the learning process) to an arbitrary given flow rate history (usually a constant flow rate history for simplicity). This flow rate history and the corresponding pressure prediction revealed the reservoir model underlying the variable PDG data.

In the previous work, a series of synthetic cases and real field cases have been used to test this approach. The method recovered the reservoir model successfully in all cases. In this paper, the method was tested under problematic data situations, including the existence of significant outliers and aberrant segments, incomplete production history, and unknown initial pressure. The results suggested that: 1) the method tolerated a moderate level of outliers and aberrant segments without any preprocessing; 2) the method could reveal the reservoir model with effective rate correction when the production history was incomplete; 3) the method could reveal the reservoir model and discover the appropriate initial pressure by using an optimization on initial pressure value when the initial pressure was unknown.
Gibbs Free Energy Minimization for Reactive Flow in Porous Media
Authors: Venkatraman Ashwin , Lake Larry W. , Johns Russell T.
Published: September 2013

Acid gases (CO2/H2S) injected in aquifers for continuous hydrocarbon production from sour gas fields (gas reserves with acid gas contaminants) can react with the ions present in the brine. The solubility predictions are then, quite different than those without reactions. Accurate solubility estimates in the presence of such reactions are integral towards developing an effective acid gas disposal strategy for continuous production from these fields. Also, the modeling of CO2 injection in oil reservoirs entails complex interplay of flow, geochemical reactions and hydrocarbon phase behavior. The geochemical reactions affect the component mole numbers, which can change the number of hydrocarbon phases and/or affect the distribution of components in them. In this research, we propose the Gibbs free energy minimization algorithm that integrates geochemical reactions and phase behavior to find equilibrium compositions for these two applications. We use this algorithm to find equilibrium compositions for not just pure phase equilibrium (without reactions) but also phase and chemical equilibrium (with reactions). While the number and composition of the hydrocarbon phases may vary; we assume all the geochemical reactions are at equilibrium. In the first application, we use this algorithm to estimate solubility of acid gases (CO2 and/or H2S) in pure water as well as CO2 solubility in high salinity brine. The algorithm predicts the solubility for binary systems of CO2- H2O and H2S-H2O at high pressures and at temperatures upto 50°C. The use of Pitzer's activity coefficient model for aqueous phase components also helps predict the solubility of CO2 in high salinity brine. In the second application for hydrocarbons, we investigate the impact of geochemical reactions on the phase distribution of CH4-CO2-H2O mixture. We observe that the geochemical reactions do not change the equilibrium phase mole fractions at 50°C in the pressure range 0.1–20 MPa.
New Approach to Identify Analogue Reservoirs
Authors: Rodriguez H. Martin , Escobar E. , Embid S. , Rodriguez N. , Hegazy M. , Lake Larry W.
Published: September 2013

The identification of analogous reservoirs is an important step in planning the development of a new field, because the information available about the new areas is usually limited or even nonexistent. Traditionally the search for analogous reservoirs has been made by experienced geoscientists, but this practice is subject to availability of this experience and the results are heavily dominated by geology. In this paper we present a systematic and unbiased procedure to search for analogous reservoirs, based on information contained in a validated large database of reservoirs parameters, both engineering and geologic. Each reservoir has its own "fingerprint" characterized by the set of its own properties, which differ from one reservoir to another. The method uses multivariate statistical techniques to find a unique and reproducible list of reservoirs with fingerprints that are most similar to the selected target. The flexibility of the method allows variation of the similarity function (weights) and evaluation of different scenarios (static, dynamic, PVT behavior, etc.).

Our method basically consists of four steps: Data Preprocessing, Key Parameters Selection, Multivariate Analysis, and Similarity Ranking. The first step consists of the analysis and preprocessing of the available database. In the second step, Key Parameter Selection, variables with largest impact on the case to be evaluated are identified. The third step, Multivariate Analysis, applies several multivariate techniques such as principal component analysis (PCA) and cluster analysis. Finally, in the Ranking step, we apply a similarity function to the group of previously selected "analogous reservoirs", generating a similarity ranking of analogous reservoirs.

To validate this new method we use the Casablanca oil field as a target reservoir. Casablanca is a mature carbonate reservoir very well known by Repsol whose experts identified four analogues for this target. The new developed method was independently applied in this case to obtain 19 analogous reservoirs sorted by similarity criteria. The maximum similarity found was 85 % for the Amposta Marino reservoir, one of the independently identified analogous reservoirs given by the business unit team. Moreover, the four analogous reservoirs previously identified by the business unit team were between the first ten positions in the similarity ranking. These results are highly encouraging as it captures the know-how of the experts and ensures a reproducible response, regardless of the user expertise.

The most relevant advantage of this new method is that it is based on a similarity function that takes into account all the weighted key parameters simultaneously, instead of sequential filters used by some commercial software. As a result, the procedure we present in this work will support the predictive search of missing properties for the target reservoir, reducing the uncertainty for decision making.
Field Deployment of Fracturing Site Sand Fill Dust Mitigation System
Authors: Anderson T. , Parks A. , Arellano J.
Published: September 2013

Use of silica sand as a proppant has grown dramatically over the last decade with the rise in production of unconventional resources. Large volumes of silica sand are used as a proppant to hold open formation fractures. The sand is pneumatically conveyed into frac sanders before being moved again into a blender where it is mixed into the fluid to be pumped down hole. During these operations, silica dust enters the air and poses hazards to those working on site. The exposure and inhalation of silica dust can cause silicosis, the most widespread industrial disease in the world. Silicosis has been known of for hundreds of years, traditionally found in workers in the sand blasting, mining and construction industries. While the causes of silicosis are known, the disease is incurable once developed. Furthermore, the disease can take up to 15 years to materialize, making workers currently exposed unaware of the potential dangers they are presently in. According to a recent U.S National Institute for Occupational Safety and Health (NIOSH) study, many frac sites exposure levels exceed, sometimes by a factor of 10, the NIOSH Recommended Exposure Limit (REL) to crystalline silica.

In an effort to combat the increasing exposure to silica dust during fracture operations dust collection equipment has been developed. SPE163528 discussed the development of this equipment and mentions other opportunities for dust mitigation. This equipment has now been deployed to the field. This paper discusses adjustments to the equipment and further realized opportunities for dust mitigation. These include helping avoid problems such as personnel over-filling the sand bins and addressing pneumatic flow rates beyond the design limit of the dust collection system.
A Simplified Slug Flow Model for Highly Viscous Oil-Gas Flow in Horizontal Pipes
Authors: Brito R. , Pereyra E. , Sarica C. , Torres C.
Published: September 2013

Typically pressure drop prediction of gas-liquid flow in pipes is carried out by mechanistic models. A proper prediction of the pressure drop requires prior identification of the flow pattern. Previous studies indicate (Gokcal, 2003 and 2008) that the most likely flow pattern for highly viscous oil is slug flow, which consists of a liquid slug region, followed by a bubble or film region. For highly viscous oils, a simplification of slug flow models is proposed based on experimental observations. This simplification is based on the fact that the pressure drop in the slug region is much larger than the pressure drop in the film region. The developed model shows fair agreement when it is compared against the data with oil viscosities from 40 to 580 cP. This model is applicable for two-phase flow Reynolds number up to 2000, which are common values in heavy oil production systems and does not require iterative solution.
An Excess-Bubble-Point-Suppression Correlation for Black Oil Simulation of Nano-Porous Unconventional Oil Reservoirs
Authors: Firincioglu T. , Ozgen C. , Ozkan E.
Published: September 2013

The average pore size in unconventional, liquids-rich reservoirs is estimated to be less than 100 nm. At this nano-pore scale, capillary forces play an important role on phase behavior that is not considered in conventional PVT studies. Confinement on phase behavior of black-oil fluids manifests itself as bubble point pressure suppression, extension of the undersaturated portion of the formation volume factor curve, and alteration of the equilibrium gas composition. Studies show that the magnitude of the bubble point suppression is more than the capillary pressure and may amount to hundreds of psi. These phenomena can be modeled through compositional solution of the phase behavior at differing gas- and oil-phase pressure values that are due to capillary pressure. However, black-oil simulators cannot perform the compositional phase behavior calculations to estimate the total bubble point suppression due to confinement. In this study a correlation that expresses the bubble point pressure suppression as a function of the capillary pressure and the solution gas oil ratio (Rs calculated through conventional PVT which is the input in black oil simulator) was developed, such that it can be used as a simulation model input. The correlation data was based on three unconventional oil samples evaluated at different saturation pressures and compositions. To use the correlation, a modified black oil simulator that can handle the PVT data at different oil- and gas-phase pressure values is required. The source code of the black oil simulator used in this study was modified to include the total bubble point suppression into the PVT calculations. The impact of the confined phase behavior on flow was quantified through simulation runs. The results showed that the grid blocks with different capillary pressure values reach the bubble point at different times. During depletion, the grid blocks with higher capillary pressure values remained in undersaturated conditions longer, impacting the gas production and pressure profiles.
Estimation of Fluid Composition from Downhole Optical Spectrometry
Authors: Indo Kentaro , Hsu Kai , Pop Julian
Published: September 2013

During formation tester operation, the use of downhole optical spectrometry has been proven to be essential for reservoir fluid characterization. Apart from the intrinsic value of fluid profiling, obtaining fluid properties downhole in real time is of particular interest since the results may impact the decision-making process during sampling and ultimately the success of the sampling operation.

A new methodology predicts petroleum fluid composition from optical spectra acquired with wireline or while-drilling formation testers. The method comprises fluid typing, computation of fluid composition and estimation of data specific uncertainty. The fluid typing algorithm is capable of categorizing a sample into three fluid types: gas, retrograde gas and oil. Based on the fluid type identified, the appropriate mapping matrix, which transforms optical spectra into compositions, is selected. The mapping matrix is derived from a database consisting of optical spectra, compositions and pressure/volume/temperature (PVT) properties of a wide variety of petroleum fluids. The outputs of the composition algorithm are the weight fractions of the hydrocarbon pseudo components, C1, C2, C3, C4, C5 and C6+, and CO2. The composition is used to estimate the gas-oil ratio (GOR) by means of an artificial neural network algorithm. As a measure of uncertainty, confidence intervals are computed for the predicted components of the composition and GOR. All results are available during acquisition of the data.

The accuracy of the algorithm in estimating composition, GOR and their associated confidence intervals was assessed by comparing the results of the predictions against laboratory-derived results. Several field data sets were analyzed and the results were compared to the results obtained by PVT laboratories on the same samples. The estimated composition and GOR showed very good agreement with PVT results. Furthermore, the algorithm provides more accurate estimates of composition and GOR than are available with current downhole optical spectrometers.
Cross-Play Shale Gas Well Performance Analysis
Authors: Nair Narayan , Miller Mark A.
Published: September 2013

Shale resource plays often present formidable reservoir management challenges, particularly with regard to capital utilization and allocation. In spite of significant efforts to measure and analyze key reservoir and completion data, uncertainty typically remains in the physical characteristics of the stimulated reservoir volume (SRV) accessed by hydraulic fracturing, namely: shale permeability, fracture spacing, SRV spatial dimensions, and gas-in-place.

In this study, well performance histories of several hundred wells spanning the Haynesville, Woodford, Barnett, Horn River, Marcellus, Fayetteville and Montney shale plays were investigated with a common and consistent analytical framework that determined: a) a well productivity measure during infinite-acting linear flow, b) completion pressure losses (between sandface and bottomhole), and c) apparent original-gas-in-place in the SRV. Parameters determined from the analyses are key indicators of the combined result of reservoir quality and hydraulic fracture performance. Results of this multi-well cross-play study provide information about both inter- and intra-play variability and commonality.

A large proportion of the wells (85%) showed prolonged periods of linear transient flow, indicative of low matrix permeabilities. Wells of higher productivities tended to go into depletion flow earlier, which could be consistent with either high matrix permeability or large fracture surface areas that are close together (complexity). Completion pressure drops were not observed as the dominant productivity-loss mechanism. Productivity of wells during infinite-acting flow normalized by the total mass of proppant used in each well, an SRV creation efficiency, and the original-gas-in-place in the SRV for all wells in this study showed log-normal distributions. The 100-day flow efficiency of the completions in these wells showed a truncated normal distribution.

Recognizing the variability in the reservoir characteristics of the studied shale plays, and SRV's that were outcomes of diverse completion practices, the observed predictability in key well performance characteristics is remarkable. The distributions presented in this paper can be used to improve well performance predictability, help identify sweet spots for drilling, establish relatively narrow ranges of a priori well performance characteristics (therefore reducing uncertainty at undeveloped well locations), improve fracturing practices, and provide support for decisions of capital allocation.
Causal Analysis and Data Mining of Well Stimulation Data Using Classification and Regression Tree with Enhancements
Authors: Bhattacharya Srimoyee , Maucec Marko , Yarus Jeffrey , Fulton Dwight , Orth Jon , Singh Ajay
Published: September 2013

The well treatment program is an important part of the field development plan, and certain variables, such as job pause time (JPT) and fracture screenout, can affect its efficiency. JPT is the time during which pumping is paused in between subsequent treatments of a job. Screenout occurs because of a sudden restriction of fluid flow inside the fracture and through the perforation. The objectives of this work are to investigate whether, from existing data, it is possible to find patterns in significant variables that affect the extreme values of JPT in a particular region and what is the most critical variable causing screenout. The answers are sought by applying a classification and regression tree (CART) to both categorical and continuous variables in the database. The practical application of CART is presented using case studies containing JPT and screenout. Significant variables are found that affect the response variables, and predictor variables are ranked in the hierarchal order of their importance. Such information can be used to control predictor variables that cause high JPT or screenout.

The results are outlined in an intuitive way, including categorical, continuous, and missing values. Because CART is a data driven, deterministic model, one cannot calculate the confidence interval of the predicted response. The confidence in results is purely based on the historical values, and the accuracy of the result produced by a tree model depends on the quality of recorded data measured in terms of volume, reliability, and consistency. The prediction capability of CART is enhanced by using the normal score transform (NST) and by dividing the large dataset into smaller groups using clustering. The approach presented in this paper analyzes a dataset under limited information and high uncertainty and should lead to developing methodology for generating proxy models to find future success indices (e.g., one for drilling efficiency or production from a fracture). This could standardize stimulation and generate decision practices to save costs in field development and the optimization process.
Experimental Investigation of Propped Fracture Network Conductivity in Naturally Fractured Shale Reservoirs
Authors: Wen Qingzhi , Jin Xiaochun , Subhash N. Shah , Li Yang
Published: September 2013

Microseismic mapping of horizontal well multi-stage fracturing of shale reservoirs has proven that the geometry of fracture is not planar as assumed/observed in conventional reservoirs, but rather a complex connected fracture network. The network is assumed to be constructed by three basic fracture types (Horizontal and vertical fractures parallel to, and vertical fracture perpendicular to flow direction - Type I, Type II, and Type III fractures respectively). A new fracture test cell is designed and constructed for investigating propped fracture network conductivity similar to the API standard fracture conductivity test cell that is presently used by the oil and gas industry.

In the experimental investigation, nitrogen gas is selected as fluid for safety reasons and also its physical properties are similar to methane gas. Marble is selected as a substitute for shale in constructing the fracture network in laboratory tests because of its similarity with shale in both permeability and wettability. Shale samples cannot be easily obtained and shale slices are difficult to prepare. A lightweight (1.5 g/cc), small size proppant (40-70 mesh) is selected because of its wide use in shale gas development and ease of transportation in the fracture network. The fracture widths of the three fracture types are assumed to be equal in the same propped fracture network. Twenty-two groups of successful experiments are selected to calibrate equipment, investigate the influence of actual fracture width, number of each fracture type, and closure stress on propped fracture network conductivity by selecting various combinations of fracture patterns, confining pressures, and proppant concentrations. Darcy's law is employed in calculating propped fracture network conductivity by introducing concepts of equivalent fracture width, equivalent proppant concentration, and equivalent fracture conductivity.

The experimental results showed that the modified API fracture conductivity test cell was calibrated well against the API standard cell. The deviations were in the range of 4.4% to 8.1%. The value of equivalent propped fracture conductivity measured by the modified API fracture conductivity test cell is acceptable. It was observed that the propped fracture network conductivity (1) decreases with increasing closure stress, and reached a limiting value when closure stress exceeded a critical value and (2) increases with increasing actual fracture width (proppant concentration). Furthermore, increasing number of Type-I and II fractures will increase propped fracture network conductivity, and Type-II fracture is more dominant than Type-I fracture, but Type-III fracture does not affect propped fracture network conductivity as significant as other two fracture types do.