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Hasanov, Zahid (BP) | Allahverdiyev, Parviz (BP) | Ibrahimov, Fuad (BP) | Mendoza, Alberto (LYTT Limited) | Thiruvenkatanathan, Pradyumna (LYTT Limited) | Noble, Lilia (LYTT Limited) | Stapley, Jonathan (LYTT Limited)
Abstract This paper discusses results from the first successful deployment of a predictive modelling technology that informs pressure optimization procedures to help minimize sand production and increase hydrocarbon production efficiency in sand prone oil wells. The technique takes variabilities in sand production observed through time across the reservoir section, inferred from downhole sand entry logs, alongside real-time sand transportation logs that monitor sand deposition in pipe as key inputs (both of which computed using a fiber optic Distributed Acoustic Sensor (DAS) based Downhole sand monitoring system). This data is then combined with other time series sensor inputs, like choke position, Down Hole Pressure (DHP) and surface flowline acoustic measurement (sand detector) to predict drawdown pressure envelopes to improve production efficiency. This paper details observations and initial field results from the first deployment of the capability in a highly deviated sand prone oil well completed with an open hole gravel pack (OHGP) completion in the BP-operated Azeri- Chirag- Gunashli (ACG) field located in the Azerbaijan sector of the Caspian Sea. The paper will detail observations and procedures used to increase oil production by over 25% and eliminate sanding risks using the technology. The proposed workflow is part of a comprehensive suite of downhole sand surveillance and management tools fueled by streaming analytics capabilities run on DAS data that have played a key role in managing sand production challenges in the ACG field. The technology has been applied numerous times for base protection, drawdown optimization and targeted remediation. In this instance, we discuss the use of the technology to (1) identify and inform the source of sand detected at surface e.g., formation or completion accumulation, (2) identify formation intervals at risk of sanding, and (3) design advisory operational procedures for production optimization.
Summary Working in the oil industry comes with unique challenges and risks, and so extra precautions and safety measures coupled with strict environmental compliance must be applied. Contrary to the common belief that strict safety enforcement could hinder smooth operations, the deployment of new technologies and enhanced solutions of processes has enabled operational excellence (OE) and improved safety performance. In this paper, we demonstrate health, safety, and environment performance improvement through implementing two main initiatives: The first category has initiatives that require less intervention or personnel; for example, the deployment of cableless pressure sensors or permanent monitoring systems in key wells to ensure continuous real-time pressure data to monitor reservoir pressure. The second category has initiatives that mitigate traditional health, safety, and environment risks; for example, through use of multiphase flow meters (MPFMs) to collect accurate and continuous flow measurements instead of traditional well testing. Optimizing operations costs while maintaining a high-level of safety is achieved through a dedicated team working in a state-of-the-art Production Operations Surveillance Hub (POSH), which enables the monitoring of wells in real time, making production optimization decisions, and ensuring a high level of well integrity via close monitoring of wells and assets.
Geoscience technology company CGG has launched SeaScope, a pollution monitoring service, as part of its growing portfolio of environmental products. SeaScope combines remote-sensing science, Earth-observation data, machine-learning, and high-performance computing to provide information on sea-surface slicks for industries to strengthen situational awareness of the interaction between offshore assets, coastal facilities, local vessel activity, and the natural marine environment. For energy companies with offshore assets, SeaScope's proactive monitoring enables the establishment of production-water baselines and provides early detection of anomalous events and third-party pollution incidents, as well as surveillance of natural seeps. It also supports the creation of a growing evidence base of responsible operations for stakeholders such as operators, regulators, investors, and insurers. SeaScope was developed with the support of the European Space Agency and a group of energy companies and emergency-response organizations.
Wu, Yinghui (Silixa LLC) | Hull, Robert (Silixa LLC) | Tucker, Andrew (Apache Corp.) | Rice, Craig (Apache Corp.) | Richter, Peter (Silixa LLC) | Wygal, Ben (Silixa LLC) | Farhadiroushan, Mahmoud (Silixa Ltd.) | Trujillo, Kirk (Silixa LLC) | Woerpel, Craig (Silixa LLC)
Abstract Distributed fiber-optic sensing (DFOS) has been utilized in unconventional reservoirs for hydraulic fracture efficiency diagnostics for many years. Downhole fiber cables can be permanently installed external to the casing to monitor and measure the uniformity and efficiency of individual clusters and stages during the completion in the near-field wellbore environment. Ideally, a second fiber or multiple fibers can be deployed in offset well(s) to monitor and characterize fracture geometries recorded by fracture-driven interactions or frac-hits in the far-field. Fracture opening and closing, stress shadow creation and relaxation, along with stage isolation can be clearly identified. Most importantly, fracture propagation from the near to far-field can be better understood and correlated. With our current technology, we can deploy cost effective retrievable fibers to record these far-field data. Our objective here is to highlight key data that can be gathered with multiple fibers in a carefully planned well-spacing study and to evaluate and understand the correspondence between far-field and near-field Distributed Acoustic Sensing (DAS) data. In this paper, we present a case study of three adjacent horizontal wells equipped with fiber in the Permian basin. We can correlate the near-field fluid allocation across a stage down to the cluster level to far-field fracture driven interactions (FDIs) with their frac-hit strain intensity. With multiple fibers we can evaluate fracture geometry, the propagation of the hydraulic fractures, changes in the deformation related to completion designs, fracture complexity characterization and then integrate the results with other data to better understand the geomechanical processes between wells. Novel frac-hit corridor (FHC) is introduced to evaluate stage isolation, azimuth, and frac-hit intensity (FHI), which is measured in far-field. Frac design can be evaluated with the correlation from near-field allocation to far-field FHC and FHI. By analyzing multiple treatment and monitor wells, the correspondence can be further calibrated and examined. We observe the far-field FHC and FHI are directly related to the activities of near-field clusters and stages. A leaking plug may directly result in FHC overlapping, gaps and variations in FHI, which also can be correlated to cluster uniformity. A near-far field correspondence can be established to evaluate FHC and FHI behaviors. By utilizing various completion designs and related measurements (e.g. Distributed Temperature Sensing (DTS), gauges, microseismic etc.), optimization can be performed to change the frac design based on far-field and near-field DFOS data based on the Decision Tree Method (DTM). In summary, hydraulic fracture propagation can be better characterized, measured, and understood by deploying multiple fibers across a lease. The correspondence between the far-field measured FHC and FHI can be utilized for completion evaluation and diagnostics. As the observed strain is directly measured, completion engineering and geoscience teams can confidently optimize their understanding of the fracture designs in real-time.
Abstract Low-frequency distributed acoustic sensing (LF-DAS) has been used for hydraulic fracture monitoring and characterization. Large amounts of DAS data have been acquired across different formations. The low-frequency components of DAS data are highly sensitive to mechanical strain changes. Forward geomechanical modeling has been the focus of current research efforts to better understand the LF-DAS signals. Moreover, LF-DAS provides the opportunity to quantify fracture geometry. Recently, Liu et al. (2020a;2020b) proposed an inversion algorithm to estimate hydraulic fracture width using LF-DAS data measured during multifracture propagation. The LF-DAS strain data is linked to the fracture widths through a forward model developed based on the Displacement Discontinuity Method (DDM). In this study, we firstly investigated the impacts of fracture height on the inversion results through a numerical case with a four-cluster completion design. Then we discussed how to estimate the fracture height based on the inversion results. Finally, we applied the inversion algorithm to two field examples. The inverted widths are not sensitive to the fracture height. In the synthetic case, the maximum relative error is less than 10% even when the fracture height is two times of the true value. After obtaining the fracture width, the fracture height can be estimated by matching the true strain data under various heights with a strong smooth weight. The error between the calculated strain and true strain decreases as the height is getting close to the true value. In the two field examples, the temporal evolutions of both width summation of all fractures and the width of each fracture show consistent behaviors with the field LF-DAS measurements. The calculated strain data from the forward model matches well with the field LF-DAS strain data. The results demonstrate the robustness and accuracy of the proposed inversion algorithm.
Shahri, Mojtaba (Apache Corp.) | Tucker, Andrew (Apache Corp.) | Rice, Craig (Apache Corp.) | Lathrop, Zach (Apache Corp.) | Ratcliff, Dave (ResFrac) | McClure, Mark (ResFrac) | Fowler, Garrett (ResFrac)
Abstract In the last decade, we have observed major advancements in different modeling techniques for hydraulic fracturing propagation. Direct monitoring techniques such as fibre-optics can be used to calibrate these models and significantly enhance our understanding of subsurface processes. In this study, we present field monitoring observations indicating consistently oriented, planar fractures in an offset-well at different landing zones in the Permian basin. Frac hit counts, location, and timing statistics can be compiled from the data using offset wells at different distances and depths. The statistics can be used to calibrate a detailed three-dimensional fully coupled hydraulic fracturing and reservoir simulator. In addition to these high-level observations, detailed fibre signatures such as strain response during frac arrival to the monitoring well, post shut-in frac propagation and frac speed degradation with length can be modeled using the simulator for further calibration purposes. Application to frac modeling calibration is presented through different case studies. The simulator was used to directly generate the ‘waterfall plot’ output from the fibre-optic under a variety of scenarios. The history match to the large, detailed synthetic fibre dataset provided exceptional model calibration, enabling a detailed description of the fracture geometry, and a high-confidence estimation of key model parameters. The detailed synthetic fibre data generated by the simulator were remarkably consistent with the actual data. This indicates a good consistency with classical analytical fracture mechanics predictions and further confirm the interpretation of planar fracture propagation. This study shows how careful integration of offset-well fibre-optic measurements can provide detailed characterization of fracture geometry, growth rate, and physics. The result is a detailed picture of hydraulic fracture propagation in the Midland Basin. The comparison of the waterfall plot simulations and data indicate that hydraulic fractures can, in fact, be very well modeled as nearly-linear cracks (the ‘planar fracture modeling’ approach).
Abstract In the present cost-constrained environment, it is critical that operators effectively complete their wells while minimizing capital expenditure. Optimization efforts focus on increasing recovery factor by managing landing zone, increasing the number of effective fractures, increasing the size of the fractures, and increasing the length of the lateral, while reducing the total number of stages and job size, without sacrificing efficient proppant and fluid delivery. The same pressure to reduce expenditure also impacts decision making on diagnostic evaluation, reducing operators to ‘free’ or low-cost feedback, like surface production rates and decline curves. Operators are responding to these challenges by utilizing a combination of lower cost, post-completion diagnostics like deployed fiber optics, downhole camera evaluation of perforations and radioactive tracers. These less expensive options allow for a broader scope and number of diagnostic inquiries, whereas a permanent fiber may prove to be cost-prohibitive, reducing diagnostic focus to one well, in one part of a play. Combining differing diagnostic technologies enhances the overall description of the well and reservoir behaviors and improves confidence in their interpretation of stimulation and production efficiency; furthermore, where a single diagnostic measurement may be unlikely to justify dramatic change in a completion strategy, a combination of data points from different domains can and does support design change that leads to rapid, real world performance improvements. Care is needed in the conclusions drawn when utilizing complimentary diagnostics due to the differences in depth of investigation and the non-unique interpretation of some data types. This paper discusses three post-completion diagnostic technologies, perforation evaluation by downhole camera, radioactive tracers, and distributed acoustic and temperature sensing (DAS+DTS) data and their respective physical measurements, strengths and weaknesses and how they can be combined to better understand well and reservoir behavior. It concludes with a review of completion optimization efforts from the Rockies area, where these post-completion diagnostic technologies were applied in the evaluation of eXtreme Limited Entry (XLE) trials. A statistical analysis of the RA tracer, downhole camera measurement of perforation area and deployed fiber optic acquisition of DAS+DTS reveals no correlation between diagnostic answers, indicating no one diagnostic measurement can accurately predict the other, such that it could substitute for that diagnostic and provide the same answer. Asking the right question can often enhance the value of diagnostic descriptions of the system in question. Those answers often lead to the next question and clear the path forward in advancing completion optimization. Complimentary diagnostics facilitate a more complete understanding of stimulation and production performance when compared, increasing confidence when they agree. When one or more appear to disagree, the different respective physical measurements and depths of investigation often reveal a more complete and complex understanding of stimulation and production efficiency. As an aggregate they provide clarity on the effect of efforts to create conductive pathways into the reservoir, allowing operators increased control over the resulting production.
Abstract In this paper, the authors examine the impacts of natural fractures on the distribution of slurry in a well with a permanent fiber installation and drill bit geomechanics data. Additionally, they propose a framework for further investigation of natural fractures on slurry distribution. As part of the Marcellus Shale Energy and Environmental Laboratory (MSEEL), the operator monitored the drilling of a horizontal Marcellus Formation well with drill bit geomechanics, and subsequent stimulation phase with a DAS/DTS permanent fiber installation. Prior to the completion, the authors used an analytical model to examine the theoretical distribution of slurry between perforation clusters from a geomechanics framework. A perforation placement scheme was then developed to minimize the stress difference between clusters and to segment stages by the intensity of natural fractures while conforming to standard operating procedures for the operator's other completions. The operator initially began completing the well with the geomechanics-informed perforation placement plan while monitoring the treatment distribution with DAS/DTS in real time. The operator observed several anomalous stages with treating pressures high enough to cause operational concerns. The operator, fiber provider, and drill bit geomechanics provider reviewed the anomalous stages’ treatment data, DAS/DTS data, and geomechanics data and developed a working hypothesis. They believed that perforation clusters placed in naturally fractured rock were preferentially taking the treatment slurry. This phenomenon appeared to cause other clusters within the stage to sand-off or become dormant prematurely, resulting in elevated friction pressure. This working hypothesis was used to predict upcoming stages within the well that would be difficult to treat. Another perforation placement plan was developed for the second half of the well to avoid perforating natural fractures as an attempt to mitigate operational issues due to natural fracture dominated distribution. Over the past several years, the industry's growing understanding of geomechanical and well construction variability has created new limited-entry design considerations to optimize completion economics and reduce the variability in cluster slurry volumes. Completion engineers working in naturally fractured fields, such as the Marcellus, should consider the impact the natural fractures have on slurry distribution when optimizing their limited-entry designs and stage plan.
Abstract Software for the simulation of the transient behavior of natural gas pipelines commercially available, however, due to their high computational demands, they do not allow real time simulations. Further, they are difficult to set up if the goal is to match measurement data from SCADA systems or compressor stations for existing pipelines. To overcome this difficulty, a state space approach is used to capture the transient behavior of the pipeline. The general approach takes a published method from the literature that derives transfer functions and state space equations from one-dimensional Navier-Stokes and extends the method to reduce uncertainty in modeling parameters. The present method is validated against results in the literature. Then, a pipeline is modeled with commercially available, well established software, and the transient behavior is simulated and the results are compared with the present method. The main contribution of the paper is the extension of the stat-space formulation to remove uncertainty in pipe-roughness assumptions through systematic estimation of friction factors. Introduction Natural Gas Pipelines are an efficient method to transport energy over large distances. The transportation of natural gas and/or blends of natural gas and hydrogen over large geographic areas requires efficient operation of compressors and other related facilities. The scheduling of flows throughout a piping network is a great challenge to control theory. Many gas pipelines are operated under unsteady operating conditions, which in turn causes significant fluctuations in the operating conditions for the compressor stations in these pipelines. These fluctuations are the result of varying demand, as well as varying gas supply. For a given pipeline segment, the gas supply pressure and flow into the pipe are subject to change as are the pressure and flow demand on the delivery side of the pipe. These conditions, as well as their timing are only predictable to a degree.