bluuebunny/crossref_metadata_2025 huggingface dataset:
Wireless Reservoir Surveillance Using Intelligent Tracers
Authors: Williams B. , Vilela A.
Published: April 2012

Today's field developments are increasingly being characterized by very complex wells in very demanding and costly operating environments. Not only are individual wells challenging, but most are part of a complex reservoir network that must be managed over an extended period.

The high cost and risks of acquiring surveillance information using conventional technology, such as production logging tools, is forcing operators to forgo acquisition of fluid inflow distribution information and manage these fields with a blurred understanding of the reservoir.

Intelligent chemical tracers are a new technology that consist of smart plastic and unique chemical compounds that are combined into a matrix that resembles strips of plastic. The matrix is designed to be sensitive to either oil or water. For example, when water sensitive matrix is contacted by water, the matrix releases its unique chemical fingerprint (tracer) at a prescribed rate. The water sensitive matrix is dormant when contacted by oil, gas or air. Oil sensitive matrix behaves in the same way.

Strips of matrix are easily adapted to any completion configuration including conventional sand screens, ICD sand screens, packers, pup joints, intelligent completions or artificial lift hardware. The matrix can be deployed in any well type including horizontal wells and multilateral wells.

Intelligent tracers are economical, easy to deploy and have none of the negative effects of radioactive isotope-based surveillance techniques. Long service life in combination with model-based interpretation techniques of tracer flowback concentrations are the main enablers that tell operators if the entire interval is flowing, where oil is entering the well and where water is entering the well.

Samples of produced fluid are analyzed for the concentration of each tracer. This data provides the operator with insight into the relative contribution of well segments and which well segment is the source of water breakthrough.

This paper will review how the technology works, recent case histories of intelligent tracer responses and the insight the operator gained from deploying the technology.
Surge and Swab Pressures in Horizontal and Inclined Wells
Authors: Srivastav R. , Enfis M. , Crespo F. , Ahmed R. , Saasen A. , Laget M.
Published: April 2012

Surge and swab pressures generated during well construction operations are critical. As thousands of wells are drilled every year, challenges associated with downhole pressure management have become more important for the oil industry. Inadequate estimation of surge and swab pressures can lead to a number of costly drilling problems such as lost circulation due to formation fracture, fluid influx resulting in kicks, breakdown of the formation at shoe due to limited kick tolerance or blowouts. An accurate surge pressure model is very important in planning drilling operations, mainly in wells with narrow safe pressure window, slimholes, low-clearance casings, deepwater, and extended-reach well applications.

Existing surge/swab pressure models assume concentric wellbore. This assumption is hardly ever valid in horizontal and inclined wells with some degree of eccentricity. Ignoring the pressure reducing effect of eccentricity on surge and swab pressures may eventually lead to underestimating the tripping speeds, and thereby increase non-productive time and operation costs. Eccentricity between the wellbore and the drillpipe adds more complexity to surge and swab pressure calculations. Recent studies have indicated that surge pressure can be significantly reduced due to eccentricity. Although the numerical investigation shows encouraging results, understanding of pressure surges in wells with eccentric annular geometry is very limited.

This paper presents the results of experimental investigations conducted to study the effects of eccentricity on surge and swab pressures. Experiments were performed in a test setup, which consists of fully transparent polycarbonate tubing, and inner pipe that moves axially using a speed controlled hoisting system. During the experiments, test fluid viscosity, trip speed, and eccentricity were varied. Experimental results were compared with predictions of existing models showing a satisfactory agreement. Results confirm that trip speed, fluid rheological properties, annular clearance and eccentricity significantly affect the surge pressure. In some cases, eccentricity can reduce surge and swab pressure by around 40%. Applying regression analysis, a generalized correlation has been developed to account for the reduction in surge pressure due to the eccentricity of the drillpipe.
Automation Master Plan Framework: Case Study
Authors: Herrera D. , Avelino J. , Sánchez J. , Díaz O. , Galán A. , Bravo C. , Rodríguez J. , Torre M.
Published: April 2012

Given the complexity and diversity of the PEMEX enterprise processes and the geographical dispersion of its facilities, the industrial automation platform has become a key element of the company's technological architecture. The automation master plan (AMP) framework includes strategies, architecture guidelines, and technological trends required to reach the enterprise production goals, with safe and environmentally responsible processes and with maximum profitability. The AMP framework includes an analysis of the automation requirements for all PEMEX business units and the development of corporate industrial automation architecture, designed to accomplish this requirements.

The industrial automation architecture was developed based on service oriented architecture (SOA). This architecture covers the various levels related to production management, from the production control and supervision systems, to the business processes automation and the presentation of the process information. Integrated asset management concepts were used to define the architecture, which were extrapolated from upstream processes to other processes in the value chain, e.g., transport, refining, gas, and petrochemical.

This paper describes the different project phases of the automation master plan, the automation architecture, and the initial benefits realized from such implementation.
Improved Reservoir Characterization of Tight Gas Sands through the 3D Integrated Reservoir Modeling of Queen City Basal, Burgos Basin, Mexico
Authors: D'Alessio S. , Muñoz L. , Ochoa A. , Garza E. , Brito F.
Published: April 2012

A real case application is presented in the following study of the methodology for the characterization of the Eocene tight gas sands located in Burgos Basin, Mexico.

The depositional arquitecture, complex mineralogy, low permeability, and diagenesis, threaten the understanding and commercial development of Queen City reservoirs. The aim of this study is to integrate the geological model, the petrophysical model, the simultaneous inversion study, and the production history as part of the 3D reservoir model workflow. The methodology can be divided into three main steps: First, a high resolution correlation, log facies analysis, stacking patters, sedimentary environments, and the creations of the 3D structural grid. Then, the petrophysical model based on the Wiland concepts calibrated with the production performance, the rock physics analysis, the geobodies, and attributes generated cross-plotting P and S Impedanceis carried out and considered as part of the elastic inversion AVO/AVA. Finally, a 3D facies and property model is developed to integrate regional trends and variogram analysis in conjunction with geobodies and attribute trends coming from the simultaneous inversion which gives a reliable spatial distribution of facies and properties. By the use of Sequetial Indicator Simulation algorithm (SIS), several facies realizations are generated and relevant sets of petrophysical properties are modeled.

The developed workflow has been applied in a case study in the Eocene tight gas sands of the Queen City Basal reservoir. A new reservoir model was created, able to discriminate shale prone zones and zones affected by diagenesis. Two main productive flux units were characterized in conjunction with the production history of this sands related to individual completions.

The contribution of the presented study is to provide a methodology of characterization of tight gas sands reservoir with complex lithology in intermediate stages of development, given importance of well and seismic data for property modeling.
Reviewing Mature Fields - A Case History
Authors: Martino Luis , Iuliano Alberto , Ucan Sezai , Hern Caroline
Published: April 2012

In Argentina, over the last decade mature field management has been of paramount importance in ensuring economic sustainability for many oil field operators. Success requires solving a specific suite of problems comprising mixed generations of technology (in particular logging tools), long and complex well histories and often the sheer size of the dataset.

The field in this case study has been in production since 1964 reaching its maximum production capacity of 32000 bpd during 1969, after which decline began. Consequent depletion from 140kg/cm2 to 20kg/cm2 drove the need for pressure support that was achieved through waterflooding which was implemented in two major campaigns during the 70's and the 80's. A total of 354 wells comprise the historical dataset with recent re-drills, extensions and infills bringing the total well count to 422. Re-evaluation of the remaining target via a series of studies carried out between 2006 and 2009 indicated an attractive opportunity for 7 spot waterflooding and saw the commencement of a massive re-development of the field.

Behaviour of recent wells has been worse than predicted. This deviation from expectation initiated a series of studies to better characterize the reservoir with the objective of re-defining targets for incremental development. Associated with these studies new geological and dynamic models were built using re-evaluated historical data integrated with information from 68 new wells and 8 new cores. In particular, the impact of textural variation and thin bed architecture on the meso-scale oil distribution was assessed allied with a range of different techniques to identify macro-scale compartmentalization. The result was an integrated model that enabled comprehensive re-evaluation of the remaining targets.

The approach used in this study to identify and characterize thin beds in this type of setting, define the impact on OOIP and determine the remaining oil in place in order to evaluate opportunities can assist many operators who experience various challenges associated with developing mature acreage.
Parallel Preconditioners for Reservoir Simulation on GPU
Authors: Liu Hui , Yu Song , Chen Zhangxin , Hsieh Ben , Shao Lei
Published: April 2012

In this paper, we present our work on developing parallel preconditioners for iterative linear solvers on NVIDIA Tesla GPU. A unified triangular solver for ILU-like preconditioners is developed. A new matrix format and the corresponding parallel algorithm are designed. Based on this triangular solver, block ILU(0), block ILUT and domain decomposition preconditioners are implemented. Numerical experiments show that these GPU based parallel preconditioners are around 8 times faster than our CPU based preconditioners.
Simulating Progressive Cavity Pump for Multiphase Flow and Production System Design
Authors: Zhang He , Li Jun , Wang Wenhao , Watters Colin , Houeto Fabien
Published: April 2012

A progressive cavity pump (PCP) characterization model is developed to predict flow characteristics under varying multiphase flowing conditions.

This paper presents a procedure for modeling PCPs and its integration to grid-based network solvers including successively accelerated substitution (SAS) and Newton-based. Our numerical study shows the latter leads to a much lower computing cost than that of its counterparts. This PCP model also provides calibration capacity on the performance curve at in-situ PVT properties.

This modeling work will assist production engineers in PCP related jobs, including: PCP surveillance, well planning, nodal analysis, and network optimization.
Development of the Brazilian Pre-Salt Fields – When to Pay for Information and When to Pay for Flexibility
Authors: Moczydlower B. , Salomão M. C. , Branco C. C. , Romeu R. K. , Homem T. R. , Freitas L. C. , Lima H. A.
Published: April 2012

The Santos Basin Pre-Salt Cluster (SBPSC), Offshore Southeast Brazil, is a unique scenario, posing great development challenges. The microbial carbonate reservoir is unusual regarding its origin and petrophysical properties; the fluids have a variable CO2 content; the few analogue reservoirs around the world do not compare in terms of volumes, water depth and distance to the coast; and there are also flow assurance issues.

Considering the importance of these reserves for the Brazilian economy and the opportunity to accelerate cash flow, Petrobras and its partners have opted for a fast track development, including extended well tests (EWTs) and production pilots. The current Petrobras Business Plan (2011–15) foresees that the SBPSC areas alone will produce over 500,000 boe/d in 2015 and over 1,100,000 boe/d in 2020. These numbers refer only to Petrobras share and do not include the transfer of rights with economic compensation from the Brazilian government to Petrobras.

Therefore, the initial development phase will have to cope with several uncertainties, mainly the subsurface ones. Some of the most relevant are the quality and the heterogeneity degree of each reservoir zone; the compositional grading of the fluids; the performance of different EOR methods; and the presence of fractures affecting the flow. How to specify and anticipate the acquisition of expensive equipment, such as FPSOs and subsea devices, with uncertainties to be clarified? When is it worth to invest in more data acquisition, such as EWTs, core and fluid sampling, extensive lab analysis or even more appraisal wells? The timing and the uncertainty reduction foreseen for each initiative must be taken into account. On the other hand, when is it better to pay for extra flexibilities, accepting the inevitable CAPEX increase? Some examples would be: smart completions and possibility to inject different chemical products in the wells; gas and water separated lines for each satellite injector; flexible subsea layout, allowing multiples strategies and the addition of more wells; FPSO plants designed to inject desulphated water, or to export, import or reinject the gas, and also to separate variable CO2 contents in the produced fluids.

This paper aims to discuss the influence of the main subsurface uncertainties in the selection of alternatives to develop the giant fields in the SBPSC, in a fast track way.
South Sen Field Dynamic Analysis, Mexico South Region
Authors: Cabrejos M. B. , Guevara L. F. , Orozco G. Sanchez
Published: April 2012

Sen field was discovered in mid 1984 with full exploration beginning in May 1987. The exploration area consisted of 30 wells, 6 of them which remain active today; reservoirs are from dolomites, where fractured Middle and upper Cretaceous limestones currently provide the majority of 'production. The field produces 40° API volatile oil with extremely low matrix porosity (0–3% average) and natural fractures as the primary production source.

A need to evaluate the fluid diffusion inside the pore system arises from well depletions rates, sudden water breakthrough, so as to find production opportunities and non-drained areas. A dynamic analysis and its integration with a productivity analysis was proposed to help us understand the reservoir dynamics and the well productivity behavior.

Well tests interpretations and matching with production rate record, the so called dynamic analysis, is nowadays one of the main reservoir characterization methods and thus, can become a very important tool to set the right reservoir developing strategy.

This paper discusses the applied methodology, for this purpose well test and production analysis specialized software were used. The first step was to interpret the buildup and draw-down well tests under a Pressure Transient Analysis outline; then, these analyses and the production record were matched to achieve an improved reservoir's model definition. Once these analyses were over, equivalent time synchronization was done to the production and pressure performance of each well, having as a basis the reservoir's model that was built from the well test interpretations. As a result, a great data matching was established thereby obtaining the reservoir's parameters, oil in place, depletion rate and production forecast to rely on better reservoir's characterization and overview, thus increasing reservoir's productivity
Sand Exclusion or Management: Multidisciplinary Approach in Decision Making
Authors: Jaimes M. G. , Quintero Y. A. , Martin D. P. , Puentes M. S.
Published: April 2012

Sand production in many oil and gas fields is a critical problem that lowers their profitability. The impact can be reduced if the analysis is approached from a multidisciplinary focus that can guide the decision making.

Based on the above, this paper focuses on developing a practical methodology, which integrates information from field and laboratory to select and evaluate alternatives of sand exclusion or management, to facilitate making of the best decision from the technical and economic point of view.

The study includes: selection of wells and quantification of costs associated with interventions by sanding problems, root cause of the problem of sand production by predictive models, charts of diagnostic and characterization of intervals with sand production, selection of alternatives to sand exclusion or Management, production modeling, technical-economic assessment of selected alternatives, implementation and subsequent evaluation of the work performed.

To accelerate the decision making process, the methodology was automated by developing a software tool, which generates standards of the information required for its application, developing of optimal workflow that reduces evaluation times by well over 50%, and creates an environment graphical friendly for the user.

The study was conducted in the formations sensitive at sand production of the fields: Lisama, Llanito, Galan, Brisas and Yarigui-Cantagallo in Colombia, and in the wells where the alternative sand exclusion or Management recommendedwas implemented, it was possible to reduce the frequency of interventions in more than 50% and increase their productivity. This paper presents the application results in wells Lisama 166, and Galan 135.

Finally, the main findings, conclusions, recommendations and field results obtained in this study are shown.
Optimizing CO2 Injection in an Offshore Field Considering Operational Constraints
Authors: Rosa M. , Branco C.
Published: April 2012

The continued increase in oil demand associated with the growing concern about the greenhouse gases has been an additional driver for CO2 injection into oil reservoirs. The application of this EOR method usually occurs at a later stage in the development of a field in which the operating surface facilities were normally not specified to manage high levels of CO2. Therefore, the aim of this work is to evaluate, by proper fluid characterization and compositional reservoir simulation, the benefits and risks of CO2 injection in a particular sector of an offshore reservoir, surrounded by production units not fully specified to deal with elevated concentrations of CO2.

The presented workflow, combining reservoir engineering analysis with production equipment aspects, can be applied to any target field for a CO2 injection project. However, it is even more relevant for mature offshore fields, where a CO2 production growth leading to the necessity of replacing all production facilities would probably make the project fail economically.

For the particular field analyzed in this article, the deployment of a production unit able to inject CO2 from an external source in an undrained region of the reservoir, hydraulically connected to an area already in production, would bring benefits not only to the region where the injection would occur but also to the adjacent area. The CO2 migration to the neighboring area decreases the levels of CO2 to be processed in the new platform plant, allowing its technical and economic feasibility, as well as increases the recovery factor of the adjoining area, without reaching levels of CO2 and gas flow rates beyond the limits of the plant already in operation. Furthermore, the reservoir's capacity to retain CO2, acting as a carbon sink, is also evaluated.

This study thus presents an integrated workflow for an optimal CO2 injection project design, considering not only the benefits in terms of recovery in the target area of the project, but analyzing the impacts and risks to surrounding areas.
A Genetic Algorithm for Gas Lift Optimization with Compression Capacity Limitation
Authors: Garcia Artur Posenato , Rosa Vinícius Ramos
Published: April 2012

Gas Lift consists of gas injection into the tubing to reduce hydrostatic pressure loss. The oil produced from each well is a function of the gas injection rate. Some wells have unstable behavior by injecting low gas lift flow rates, on the other hand, excessive injection rates causes loss production due to its high friction pressure drop. Therefore the gas lift flow rate must be kept in a bounded interval. The objective of gas lift optimization is to allocate a limited amount of gas to a number of wells in order to maximize oil production or project revenue. Evolutionary algorithms were applied to achieve optimal production rates and decide which well must be closed when the compression capacity is severely reduced.

The FPSO considered in this study is equipped with three compressors to produce 16 wells with gas lift and export gas. Eventually, one or two compressors can have a downtime due to maintenance requirements or failures. In this case, at least one well has to be closed. The algorithm was developed to optimize the production when the platform compression capacity was reduced and decide which well should be shut-in. It takes into account not only the total amount of gas available but also the gas lift pressure, which can change along time.

The algorithm could solve a practical gas lift optimization problem and was able to determine automatically which wells had to be closed whenever the total available gas was not enough to operate all wells simultaneously. In case of total available gas be enough that all wells could produce, the results obtained by this genetic algorithm were equivalent to any ordinary optimization algorithm.

The production optimization is an important issue even during abnormal operational conditions. The water cut increases with the aging of wells and the gas lift flow rate demand also increases. Severe compression limitations are undesirable but they can eventually occur.
Uncertainty History Matching and Forecasting, a Field Case Application
Authors: Becerra G. G. , Modenesi A. P. , Lisboa E. F.
Published: April 2012

Geological, reservoir, economical and technological uncertainties have an effect on decision making and consequently on reserves development plans. Quantifying the impact of these uncertainties can make this process more reliable. A great difficulty to achieve this in practice is the variability and complexity of workflows available to manage uncertainty using numerical simulation.

The inaccuracy, high uncertainty or lack of reliable data yields risk to the forecasting process, making the calibration of the dynamical model with the field production data indispensable. History matching is an inverse problem and, in general, different combinations of reservoir attributes can lead to acceptable solutions, especially due to the high degree of uncertainty of these attributes. A set of solutions that respect the observed data may lead to different prediction scenarios.

The objective of this work is the integration of history matching with probabilistic analysis of representative scenarios. A methodology that allows the recognition of well-calibrated models within an acceptable deviation is used. This procedure helps to identify the critical uncertain parameters and their possible variation in order to estimate the representative reserve range. The goal is not to find the best deterministic match, but rather to show how the calibration process allows a mitigation of identified uncertainties.

A real case based on a reservoir from Campos Basin in Brazil was used. A 14 year historical period followed by a 12 year forecast period was considered, allowing verification and validation, at a global level, of the proposed procedure in a complex dynamic model. Two different commercial softwares were used, in order to demonstrate the advantages and restrictions of each approach. Distribution variations of the responses in time were evaluated by Latin Hypercube sampling and Monte Carlo propagation on validated proxy models.

The proposed methodology allows: (1) to reduce the range of possible models taking into account the observed data; (2) to identify the existent uncertainty as a function of observed data; (3) to reduce the uncertainty range of critical reservoir parameters; (4) to increase confidence in production forecast. One contribution of this work is to present a quantitative approach for increasing the reliability of reservoir simulation as an auxiliary tool in decision making processes in order to reduce the associates risk and to maximize development opportunities.
Recent Advances in Dynamic Modeling of Naturally Fractured Reservoirs
Authors: Camacho-Velázquez R. , Vásquez-Cruz M. , Fuentes-Cruz G.
Published: April 2012

Modeling of naturally fractured reservoirs (NFR) is a challenging problem which occurs frequently in reservoir engineering. Rock matrix, natural fractures, vugs, and also micro-fractures, constitute these NFR. Furthermore, it is well known that vugs effect on permeability is related to their connectivity. Likewise, in certain cases NFR exhibit fractures at different scales with poor fracture connectivity and disorderly spatial distribution of them. Thus, it is important to consider other alternatives for characterizing these heterogeneities in a more efficient way than traditional approaches. One of the reasons which drive to find solutions to these challenges is because these geological formations contain more than 60% of the world's remaining oil. Therefore, in order to exploit in a more efficient way the remaining hydrocarbons reserves, it is frequently necessary to face greater reservoir characterization and modeling challenges than those ones existing when these reservoirs started their productive life. This is even more relevant when a pressure maintenance project or an IOR/EOR process is planning to be implemented.

This work summarizes recent advances that address different dynamic modeling approaches, taking into account NFR's features like the presence of vugs and fractures at multi scales with a non-uniform spatial distribution. Thus, it is demonstrated the advantages of these continuum approaches to model anomalous behavior that cannot be reproduced by the conventional Warren and Root dual porosity model in order to obtain good-quality history matches for these systems. Also, the characterization challenges that the proposed models pose to the user are reviewed. Finally, some insights aimed to improve the proposed modeling techniques are provided.
New Artificial Lift System Using Coiled Tubing and Reciprocating Downhole Pumps for Heavy and Viscous Oil
Authors: Flores-Avila F. S. , Riaño J. M. , Javier-Martinez M. , Hammond T. , Cantu J. , Ramos J.
Published: April 2012

The use of coiled tubing as an artificial-lift mechanism has been very popular for lifting oil wells as velocity strings (siphon strings) and also removing water and condensate from gas wells. The effect of reducing the effective flowing area, increasing fluid velocity and therefore unloading the well is no longer the only lifting mechanism for this particular application. Reciprocating movement provided by a surface hydraulic operated unit is transmitted by the coiled tubing to a down-hole pump to assist in the lifting process. Therefore for low productivity wells in which the fluid velocity is significant below the minimum or critical velocity to prevent a well from loading up, the down-hole pump will achieve the flowing condition. Utilizing coiled tubing as the motion transmitter to the down-hole pump increases the benefits already explored by the use of continuous rod for SRP applications, by also providing a flow path from surface to bottom.

Through this flow path, chemical injection down the coiled tubing, and returning by the annular space between the coiled tubing and the 2 7/8" tubing string can be achieved while pumping the well. Chemicals pumped can be either viscosity reducers, corrosion inhibitors or any other needed to achieve optimum production. Also this flow path can be used to wash out sand or debris present inside the tubing string in an easy, fast and economical way. Also the potential use of pumping up through the inside of the coiled tubing or the back side (annular space between the coiled tubing and the production string) has been investigated with satisfactory results in this application.

The system has been successfully tested in four oil wells in North Mexico (two of them in the Chicontepec project) with densities up to 13.9 °API and viscosities up to 6464 centipoises. System components, selection criteria, design, execution, evaluation and lessons learned during this first time application are discussed in this paper. Based on the observed results, this technology is being considered as a technical and economical alternative to develop the heavy and viscous oil wells in the area.
Modeling Condensate Banking in Lean Gas Condensate Reservoirs
Authors: Huerta V. A. , Lanchimba A. , Porlles J. W.
Published: April 2012

Gas condensate reservoirs show a complex behavior when they are produced below dew point pressure under isothermal conditions, due to the presence of a two-phase system, and the appearance of a condensate banking phenomena. Recent gas condensate field discoveries in Peru exhibited initial reservoir pressures slightly higher than dew point; as PVT reports indicated that retrograde liquid saturation would not exceed 4%, condensate drop-out was not presumed to be a significant problem affecting well productivity and production performance, and indeed, strategies to face this problem have been currently delayed

Initial multirate tests run in the Peruvian gas condensate fields did show only a slightly indication of liquid drop-out in NIA formation (less than 5%), but some features of the existence of condensate banking were noticed in NOI and ENE reservoirs. As a consequence, it is worth to study the condensate drop-out phenomena as in many cases, it causes a permanent reduction in well productivity, and eventually, in recovery factor, even though is partially compensated by capillary number effects.

An integrated approach to model the condensate banking phenomena at well and fullfield scales, over the time, in Peruvian gas condensate fields is proposed by the combination of two powerful tools: well testing analysis and numerical compositional simulation; while the transient testing analysis, supported by a deconvolution algorithm, is used to evaluate "snapshots" of the three or four regions representing the various mobility zones around the wellbore, the compositional simulation allows predicting how the condensate banking will evolve in the future, and how this phenomena will affect production performance. Preliminary results predict a reduction of gas and oil production and recovery between 3% and 5%.
Measurement, Modeling, and Diagnostics of Flowing Gas Composition Changes in Shale Gas Wells
Authors: Freeman C. M. , Moridis G. J. , Michael G. E. , Blasingame T. A.
Published: April 2012

Few attempts have been made to model shale gas reservoirs on a compositional basis. Multiple distinct micro-scale physical phenomena influence the transport and storage of reservoir fluids in shale, including differential desorption, preferential Knudsen diffusion, and capillary critical effects. Concerted, these phenomena cause a measureable compositional change in the produced gas over time.

We developed a compositional numerical model capable of describing the coupled processes of diffusion and desorption in ultra-tight rocks as a function of pore size. The model captures the various fracture configurations believed to be induced by shale gas fracture stimulations. By combining the macro-scale (reservoir-scale fractures) and micro-scale (diffusion through nanopores) physics, we show how gas composition changes spatially and temporally during production.

We compare our numerical model against measured gas composition data obtained at regular intervals from shale gas wells. We utilize the characteristic behavior illustrated in the model results to identify and to define features in the measured data. We present a workflow for the integration of measured gas composition data into production data analysis tools in order to develop a more complete well performance diagnostic process.

The onset of fracture interference in horizontal wells with multiple transverse hydraulic fractures is shown to be uniquely identified by distinct fluctuations in the flowing gas composition. Using these measured composition data, the timescale and durations of the transitional flow regimes in shales are quantified, even for high levels of noise in the rate and pressure data. Reservoir properties are inferred from the integration of the compositional shift analysis of this work with modern production analysis.

This work expands the current understanding of well performance for shale gas to include physical phenomena that lead to compositional change. This may be used to optimize fracture and completion design, improve well performance analysis and provide more accurate reserves estimation.

This work demonstrates a numerical model which captures multicomponent desorption, diffusion, and phase behavior in ultra-tight rocks. We identify and validate diagnostic trends via high-resolution composition, saturation and pressure maps. We provide a workflow for incorporating measured gas composition data into modern production analysis.
Sizing of Pipelines for Gas-Condensate by Multiphase Dynamic Simulation, Based in Minimum, Medium and Maximums Flowrates
Authors: Martinez-Ortiz V.
Published: April 2012

In this paper a methodology based in multiphase dynamic simulation to size gas-condensate pipelines is presented. This method considers minimum, medium and maximum forecasted field flowrates. Sizing the pipeline considering only the maximum flowrate can result in oversizing the pipeline diameter. An oversized pipeline can cause operational problems when the field's production declines. The multiphase dynamic simulation allows evaluating the flow stability for minimum and medium forecasted flowrates, where the steady state condition may not be defined.

In this paper, this methodology was applied to size a pipeline in South America's gas condensate fields. Previously, these pipelines were oversized using only steady-state tools.
Geomechanics Characterization of the Clastics and Carbonates Formation of Southern Fields of Mexico (2005 – 2009)
Authors: Tellez C. P. , Elisabeth F. , Bentosa E. , Munoz D. , Cortes C.
Published: April 2012

The geological structures to drill and reach the producing reservoir of the South region of Mexico are very complex. They can vary from deep fractured carbonates reservoir at more than 7000 m true vertical depth, anticline uplifted by salt or/and shale dome themselves inducing abnormal pressure up to 2.2 gr/cc of equivalent density in the overlying formation. The geological complexity of the south region is reflected also in its geo-pressures, geo-stresses and geomechanical properties.

Since early 2000 Petrόleos Mexicanos (PEMEX) has considered the Geomechanics discipline as a key component for their future economic success. With the urgent need to improve recovery, more complex wells are being drilled and PEMEX has taken the challenge to have geomechanics analysis for any well that will cost more than 10 Million of dollars. This strategy has been translated with training of key personnel, geomechanical core campaign and geomechanics studies included into their drilling program. Since 2006, more than fifty geomechanics studies (analytical and numerical) have been carried out in the south region of Mexico and have been incorporated to mitigate drilling risk and optimize well design. Velocity analysis, Geomechanics core test interpretation, caving interpretation, breakouts and induced fracture analysis from image logs, direct pressure measurements, leak off test and mini-frac interpretation are some of the different information used to calibrate the geomechanics studies.

This paper refers to the regional compilation, findings and results of the 50 geomechanics studies conducted in the different fields of the south region between 2006 and 2010 and its impact on the well design of exploratory and development locations. The paper presents to the industry, the methodology used for their construction, illustrated by the data used for their calibration and how they were successfully used for well design and real time decision with selected post mortem analysis for some well. Finally the results of the geomechanical studies (Strength, overpressure and stress anisotropy) have been mapped regionally to forecast the geomechanics behavior in the entire south region of Mexico to optimize the drilling of future well locations.
Methodology to Quantify the Value of Information Incorporating Operational Flexibility
Authors: Bovolenta Humberto D. , Munerato Fernando P. , Schiozer Denis J.
Published: April 2012

At the beginning of field development, many questions regarding the reservoir structural model still remain and it is necessary to mitigate this uncertainty and associated risk before the final field development plan proposition. Mitigation of risks and uncertainties can be done in two ways: through additional information acquisition and operational flexibility, but both have limitations. Information has value within a project up to the point where the benefits obtained do not outweigh its acquisition cost. Flexibility may not be viable due to the impossibility of practical changes in the production strategies or in the facilities when these are already in operation. The value of information (VOI) and value of flexibility (VOF) are resources capable of quantifying the relevance of information and flexibilities in reducing project risk, as demonstrated by the methodology proposed by Xavier (2004). However, this methodology considers fixed production strategies, which may significantly impact the value of information, overestimating it because it does not incorporate future flexibility. Thus, the objective of this paper is to improve this methodology through the implementation of an assisted automated process for strategy selection and optimization, incorporating operational flexibility to the project by reducing the number of dry wells and through a more accurate dimensioning of the production strategies and facilities. The methodology is applied to one simple case, where the only uncertain attribute is the structural model, aimed at the validation of the automated methodology. The results indicate that, in the initial phase of development, the more accurate design of the production strategies and facilities has a direct impact on the expected monetary value of the project, which is reflected in the VOI and in the decision analysis, increasing the accuracy and the value of these tools in projects with a high degree of associated uncertainty.
Evaluation of Multifractures Through Unconventional Log Using Gamma Functions, Mineralogy and Fracture Migration in Laminated Sandstone of Chicontepec's Formation, Chicontepec Channel, Mexico
Authors: Garcia S. Gomez , Estrada E. , Rodriguez L. , Vargas A. , Gomez G. , Picon O. , Estrada J. , Zarate Heriberto , Salazar A. , Tineo F. , Quediman B.
Published: April 2012

Chicontepec Basin has more than 80% of reserves in the North of Mexico; however, due to the complexity of the site, only contributes 25% of total production in the region. Considering the complexity of lithology, variation and discontinuity of facies and petrophysical conventional evaluation that do not identify: effective porosity, quantification irreducible water saturation, water moving, type of oil, identification of facies, it is proposed to use a methodology which, in addition to conventional calculations, must achieve the quantification of the fractions of porosity, movable fluid differentiate the irreducible, identify areas of low resistivity but hydrocarbon storing and integrating the results of the analysis with the sedimentary facies, gamma functions, determination the volume of shale and identification of areas of least resistance to fracturing identified through descriptions of cores, and extrapolate to other wells with less information through neural networks.

Implementation of these unconventional logs (NMR, Mineralogy and cross dipole acoustic) aims to characterize in detail the site, minimizing the uncertainty associated with the results obtained with conventional petrophysical evaluations made only from basic logs. The generation of Gamma functions (inversion of T2 spectrum with gamma functions), Laminar Disperse and Structural Clays and Fracture Analysis of Migration allows us to optimize the selection of intervals allowing for greater accuracy when shooting, fracturing and finish well. Additionally, allows more accurate to estimate reserves to define areas containing oil and which could not be identified with conventional logs.

Have fractured more than 20 wells following this methodology with an average of between 300 to 600 bpd and 4 wells surpassed the 800 bpd
Using Neural Networks for Determining Hydrocarbons Presence from Well Logs: A Case Study for Alagoas Basin
Authors: Fernandes M. A.
Published: April 2012

This work proposes a method to determine oil, gas and water presence in reservoirs directly from commonly measured well log parameters, such as resistivity, gamma-ray, density and neutron, by using Artificial Neural Networks (ANN). The wells from the oil field approached in this case study require frequent workover jobs to put their multiple zones in production one after another as soon as they become depleted. Once this oil field is segmented in hundreds of hydraulically isolated reservoirs containing small oil volumes, a procedure for identification of the fluids contained in the reservoirs crossed by a well can be of great value to make routine decisions (regarding evaluations and perforations) faster and more accurate.

The work started based on the observation that zones with different fluids (or the absence of fluids) show characteristics sufficiently particular in the cited logs that make possible their classification by an artificial intelligence algorithm. The ANN approach is chosen considering its capability of working with a non-linear problem in which some uncertainties are also present, based on algorithms with relatively simple implementation.

A characteristic of this method is that the ANN can be trained with data points of a specific zone, block or area, which means adjusting itself to this specific data set, learning its particularities, what leads to more accurate results when used to classify other zones with similar characteristics. The method's applicability increases in mature fields presenting a large number of logged wells with perforated and tested zones allowing validation of the information used in the supervised learning of the ANN.

For the training and validation of a Multi Layer Perceptron (MLP) Neural Network, 160 data points were used with depth information and the corresponding Gamma Ray, Resistivity, Density and Neutron log values, along with fluid identifications based on the results of logs and perforations. These data points came from two wells of Alagoas Basin, Brazil.

In the tests performed in this work, the ANN presented a generalization capability after extracting information from the training data, leading to a good confidence in the classification results for a testing data set.
Predictive Analytics: Development and Deployment of Upstream Data Driven Models
Authors: Holdaway Keith R.
Published: April 2012

The oil and gas industry is engulfed by a plethora of disparate data collated across multiple geoscientific and siloed disciplines. Moreover, the data are growing exponentially as digital oilfields are being implemented in some fashion to manage conventional and unconventional assets. Performing exploratory data analysis and generating data marts tailored to specific advanced analytical workflows are cornerstones to enable development and deployment of predictive models that are data driven, both in real-time and across historical data sets.

To build data driven models that can predict under uncertainty is essential to rapidly identify multi-dimensional parameters in a multivariate environment and thus surface hidden patterns and relationships in data that subsequently reduce time and resources in the critical decision-making cycles. With improved workflows and advances in High Performance Computing, it is now possible to ascertain risk and quantify uncertainty for very large populations of data without sampling and losing knowledge garnered by predictive models driven by the data and not by empirical petroleum engineering algorithms or deterministic methodologies. By marrying the stochastic with the interpretive school of thought, the upstream community can maintain robust data driven models that are kept current as new data are introduced.

This paper draws upon two case studies that ameliorate the path from raw data to invaluable knowledge. We shall look at a suite of predictive models driven by real-time data that were built upon patterns surfaced in historical data. These models have been implemented to identify optimized drilling and production strategies in the North American tight gas plays and acid stimulation strategies in the Gulf of Mexico.