|Theme||Visible||Selectable||Appearance||Zoom Range (now: 0)|
Senters, Chad (ProTechnics, A Core Laboratories Company) | Jayakumar, Swathika (ProTechnics, A Core Laboratories Company) | Warren, Mark (ProTechnics, A Core Laboratories Company) | Wells, Mike (ProTechnics, A Core Laboratories Company) | Harper, Rachel (ProTechnics, A Core Laboratories Company) | Leonard, Richard (ProTechnics, A Core Laboratories Company) | Woodroof, Robert (ProTechnics, A Core Laboratories Company)
Abstract The application of data science remains relatively new to the oil and gas industry but continues to gain traction on many projects due to its potential to assist in solving complex problems. The amount and quality of the right type of data can be as much of a limitation as the complex algorithms and programing required. The scope of any data science project should look for easy wins early on and not attempt an all-encompassing solution with the click of a button (although that would be amazing). This paper focuses on several specific applications of data applied to a sizable database to extract useful solutions and provide an approach for data science on future projects. The first step when applying data analytics is to build a suitable database. This might appear rudimentary at first glance, but historical data is seldom catalogued optimally for future projects. This is especially true if specific portions of the recorded data were not known to be of use in solving future problems. The approach to improving the quality of the database for this paper is to establish requirements for the data science objectives and apply this to past, present and future data. Once the data are in the right "format", the extensive process of quality control can begin. Although this part of the paper is not the most exciting, it might be the most important, as most programing yields the same "garbage in = garbage out" equation. After the data have found a home and are quality checked, the data science can be applied. Case studies are presented based on the application of diagnostic data from an extensive project/well database. To leverage historical data in new projects, metrics are created as a benchmarking tool. The case studies in this paper include metrics such as the Known Lateral Contribution (KLC), Heel-to-Toe Ratio (HTR), Communication Intensity (CI), Proppant Efficiency (PE) and stage level performance. These results are compared to additional stimulation and geological information. This paper includes case studies that apply data science to diagnostics on a large scale to deliver actionable results. The results discussed will allow for the utilization of this approach in future projects and provide a roadmap to better understand diagnostic results as they relate to drilling and completion activity.
Zhu, Zuyang (Sinopec Research Institute of Petroleum Engineering) | Zhao, Jinhai (Sinopec Tech Houston Center) | Mulunjkar, Amol (Sinopec Tech Middle East LLC) | Rached, Rached (Sinopec Tech Middle East LLC) | Gramajo, Eduardo (Sinopec Tech Middle East LLC) | Li, Fengbo (Sinopec Research Institute of Petroleum Engineering) | Wang, Zhifa (Sinopec Tech Middle East LLC) | Shi, Zhaorui (YU Technologies Inc.) | Zhang, Wei (Sinopec Research Institute of Petroleum Engineering) | Zhao, Weishu (Sinopec Tech Middle East LLC)
Abstract The measurement of the drilling parameters such as temperature and pressure helps mitigate drilling-related issues and optimize drilling operations on a cost-effective basis. Multiple technologies can measure these parameters; however, the current tools suffer from low bandwidth, associated high cost, and limited measurement locations near the drill bit. This reduced accuracy and transmission rate while drilling can be improved using intelligent microchip tracers and micro-memory balls. These tools can measure the temperature and pressure across an entire wellbore. The proposed tracers include a microprocessor-based circuit board equipped with sensors, a communication antenna, and a rechargeable battery, all protected from the harsh downhole environment through a robust composite material. The advanced microchip tracers and micro-memory ball technologies were tested in the field and provided innovative measurement platforms. The field tests were conducted in various environments, including oil and gas wells, deviated wells, multiple hole sizes, varied fluid densities, and different BHA (Bottom Hole Assembly) geometries. During the operation procedures, the tracers travel in the drilling strings through the drill bit and return to the surface across the annulus. The data is then exported from the tracers for a quasi-real-time analysis. The results showed high success rates, four out of six microchips were successfully retrieved, and the data was made available for immediate analysis. This paper explains the challenges faced during the logging and interpretation of the data needed to define the wellbore characteristics for efficient drilling processes. The developed time-stepping algorithm correlates the measurement timestamp with the calculated depth. Lastly, the report summarizes the highlights of the tracers in terms of density, release mechanism, and collection method.
Ow, Hooisweng (Aramco Services Company) | Chang, Sehoon (Aramco Services Company) | Thomas, Gawain (Aramco Services Company) | Wang, Wei (Aramco Services Company) | Mashat, Afnan A. (Saudi Aramco PE&D) | Shateeb, Hussein (Saudi Aramco PE&D)
Abstract The development of automatable high sensitivity analytical methods for tracer detection has been one of the most central challenges to realize ubiquitous full-field tracer deployment to study reservoirs with many cross-communicating injector and producer wells. Herein we report a tracer analysis approach, inspired by strategies commonly utilized in the biotechnology industry, that directly addresses key limitations in process throughput, detection sensitivity and automation potential of state-of-the-art technologies. A two-dimensional high performance liquid chromatography (2D-HPLC) method was developed for the rapid fluorescence detection and simultaneous identification of a class of novel barcoded tracers in produced water down to ultra-trace concentration ranges (<1ppb), matching the sensitivity of tracer technologies currently used in the oil industry. The sample preparation process throughput was significantly intensified by judicious adaptations of off-the-shelf biopharma automation solutions. The optical detection sensitivity was further improved by the time-resolved luminescence of the novel tracer materials that allows the negation of residual background signals from the produced water. To showcase the potential, we applied this powerful separation and detection methodology to analyze field samples from two recent field validations of a novel class of optically detectable tracers, in which two novel tracers were injected along with a benchmarking conventional fluorobenzoic acid (FBA)-based tracer. The enhanced resolving power of the 2D chromatographic separation drastically suppressed the background signal, enabling the optical detection of a tracer species injected at 10x lower concentration. Further, we orthogonally confirmed the detection of this tracer species by the industry standard high-resolution accurate mass spectrometry (HRAM) technique, demonstrating comparable limits of detection. Tracer detection profile indicated that the transport behavior of the novel optical tracers through highly saline and retentive reservoir was similar to that of FBAs, validating the performance of this new class of tracers. Promising steps toward complete automation of the tracer separation and detection procedure have drastically reduced manual interventions and decreased the analysis cycle time, laying solid foundation to full-field deployment of tracers for better reservoir characterizations to inform decisions on production optimization. This paper outlines the automatable tracer detection methodology that has been developed for robustness and simplicity, so that efficient utilization of the resultant high-resolution tracer data can be applied toward improving production strategy via intelligent and active rate adjustments.
Abstract Miscible HC-WAG injection is a globally implemented EOR method and seems robust in so many cases. Some of the largest HC-WAG projects are found in major carbonate oil reservoirs in the Middle-East, with miscibility being the first measure to expect the success of a HC-WAG injection. Yet, several miscible injection projects reported disappointing outcomes and challenging implementation that reduces the economic attractiveness of the miscible processes. To date, there are still some arguments on the interpretation of laboratory and field data and predictive modeling. For a miscible flood, to be an efficient process for a given reservoir, several conditions must be satisfied; given that the incremental oil recovery is largely dependent on reservoir properties and fluid characteristic. Experiences gained from a miscible rich HC-WAG project in Abu Dhabi, implemented since 2006, indicate that an incremental recovery of 10% of the original oil in place can be achieved, compared to water flooding. However, experiences also show that several complexities are being faced, including but not limited to, issues of water injectivity in the mixed wettability nature of the reservoir, achieving miscibility conditions full field, maintaining VRR and corresponding flow behavior, suitability of monitoring strategy, UTC optimization efforts by gas curtailment and most importantly challenges of modeling the miscibility behavior across the reservoir. A number of mitigation plans and actions are put in place to chase the positive impacts of enhanced oil recovery by HC-WAG injection. If gas injection is controlled for gravity and dissolution along with proper understanding on the limitations of WAG, then miscible flood will lead to excellent results in the field. The low frequency of certain reservoir monitoring activities, hence less available data for assessment and modeling, can severely bound the benefits of HC-WAG and make it more difficult to justify the injection of gas, particularly in those days when domestic gas market arises. This work aims to discuss the lessons learned from the ongoing development of HC-WAG and attempts to comprehend miscible flood assessment methods.
Abstract Over the past decade, commercially available inflow tracers have been increasingly used to permanently monitor lower completions without the need for intervention. They have been designed to release selectively to oil or water, typically for clean-up verification, inflow quantification and identifying the location of water breakthrough in oil reservoirs. Naturally, there has been an industry demand and requirement to develop inflow gas tracers to monitor gas reservoirs and identifying the location of gas breakthrough in oil reservoirs. In a green field development, it is important to obtain as much measurements as possible to understand completion efficiency and guide reservoir management decisions. This paper presents the first commercial installation of inflow gas tracer technology that has been deployed in a dry gas field by HESS Malaysia in open hole stand-alone screen completions. It discusses the original monitoring objectives of this application in a full field development and how they evolved due to the gas tracer capabilities and the need for early well and field information. This paper will also discuss the retrofit screen design that allowed the gas tracers embedded in a polymer matrix called gas systems (GS) to be installed inside premium mesh screens. At the wellsite, sampling campaign adjustments were executed depending on the flowing conditions during the clean-up, restarts to obtain relative flow contribution and inflow performance under multi-rate testing conditions. Using a structured approach, the inflow gas monitoring project included feasibility studies, well candidate selection, lessons learnt and developed best practices based on installations in six producing wells in the North Malay Basin (NMB).
Abstract Geochemical data in produced water contain important reservoir information but are seldomly exploited, especially for the nonconservative chemicals. Some conservative chemical data have been integrated in history matching workflow to obtain better knowledge of reservoirs. However, assuming reservoir chemicals being conservative is impractical because most chemicals are involved in interactions with other chemicals or reservoir rock, and mistakenly regarding nonconservative chemicals as being conservative can cause large error. Nevertheless, once the interactions can be accurately described, nonconservative chemical data can be used to obtain more reservoir information. In this work, a new physicochemical model is proposed to describe the transport of natural nonconservative chemicals (barium and sulfate) in porous media. Both physical reactions, such as ion adsorption and desorption, and chemical reactions, such as barite deposition, are integrated. Based on the new model, the ensemble smoother with multiple data assimilations (ES-MDA) method is employed to update reservoir model parameters by assimilating oil production rate, water production rate, and chemical data (barium and sulfate concentration). Data assimilation results show that integrating geochemical data in ES-MDA algorithm yields additional improvements in estimation of permeability. Besides, clay content distribution, which is critical in injection water breakthrough percentage calculation, can be accurately estimated with relative root mean square error (rRMSE) being as small as 0.1. However, mistakenly regarding nonconservative chemicals as conservative can cause large errors in reservoir parameters estimation. Accurately modeling the chemical interactions is crucial for integrating chemical data in history matching algorithm.
Abstract Conventional downhole dynamic characterization is based on data from standard production logging tool (PLT) strings. Such method is not a feasible option in long horizontal drains, deep water scenarios, subsea clusters, pump-assisted wells and in presence of asphaltenes/solids deposition, mainly due to high costs and risk of tools stuck. In this respect, intrawell chemical tracers (ICT) can represent a valid and unobtrusive monitoring alternative. This paper deals with a new production allocation interpretation model of tracer concentration behavior that can overcome the limitation of standard PLT analyses in challenging environments. ICT are installed along the well completion and are characterized by a unique oil and/or water tracer signature at each selected production interval. Tracer concentration is obtained by dedicated analyses performed for each fluid sample taken at surface during transient production. Next, tracer concentration behavior over time is interpreted, for each producing interval, by means of an ad-hoc one-dimensional partial differential equation model with proper initial and boundary conditions, which describes tracer dispersion and advection profiles in such transient conditions. The full time-dependent analytical solutions are then utilized to obtain the final production allocation. The methodology has been developed and validated using data from a dozen of tracer campaigns. The approach is here presented through a selected case study, where a parallel acquisition of standard PLT and ICT data has been carried out in an offshore well. The aim was to understand if ICT could be used in substitution of the more impacting PLT for the future development wells in the field. At target, the well completion consists of a perforated production liner with tubing. The latter, which is slotted in front of the perforations, includes oil and water tracer systems. The straightforward PLT interpretation shows a clear dynamic well behavior with an oil production profile in line with the expectations from petrophysical information. Then, after a short shut-in period, the ICT-based production allocation has been performed in transient conditions with a very good match with the available outcomes from PLT: in fact, the maximum observed difference in the relative production rates is 5%. In addition, the full analytical solution of the ICT model has been fundamental to completely characterize some complex tracer concentration behaviors over time, corresponding to non-simultaneous activation of the different producing intervals. Given the consistency of the independent PLT and ICT interpretations, the monitoring campaign for the following years has been planned based on ICT only, with consequent impact on risk and cost mitigations. Although the added value of ICT is relatively well known, the successful description of the tracer signals through the full mathematical model is a novel topic and it can open the way for even more advanced applications.
Abstract Tracers are practical tools to gather information about the subsurface fluid flow in hydrocarbon reservoirs. Typical interwell tracer tests involve injecting and producing tracers from multiple wells to evaluate important parameters such as connectivity, flow paths, fluid-fluid and fluid-rock interactions, and reservoir heterogeneity, among others. The upcoming of nanotechnology enables the development of novel nanoparticle-based tracers to overcome many of the challenges faced by conventional tracers. Among the advantages of nanoparticle-based tracers is the capability to functionalize their surface to yield stability and transportability through the subsurface. In addition, nanoparticles can be engineered to respond to a wide variety of stimuli, including light. The photoacoustic effect is the formation of sound waves following light absorption in a material sample. The medical community has successfully employed photoacoustic nanotracers as contrast agents for photoacoustic tomography imaging. We propose that properly engineered photoacoustic nanoparticles can be used as tracers in oil reservoirs. Our analysis begins by investigating the parameters controlling the conversion of light to acoustic waves, and strategies to optimize such parameters. Next, we analyze different kind of nanoparticles that we deem potential candidates for our subsurface operations. Then, we briefly discuss the excitation sources and make a comparison between continuous wave and pulsed sources. We finish by discussing the research gaps and challenges that must be addressed to incorporate these agents into our operations. At the time of this writing, no other study investigating the feasibility of using photoacoustic nanoparticles for tracer applications was found. Our work paves the way for a new class of passive tracers for oil reservoirs. Photoacoustic nanotracers are easy to detect and quantify and are therefore suitable for continuous in-line monitoring, contributing to the ongoing real-time data efforts in the oil and gas industry.
Chen, Hsieh (Aramco Services Company: Aramco Research Center–Boston) | Chang, Sehoon (Aramco Services Company: Aramco Research Center–Boston) | Thomas, Gawain (Aramco Services Company: Aramco Research Center–Boston) | Wang, Wei (Aramco Services Company: Aramco Research Center–Boston) | Mashat, Afnan (Saudi Aramco) | Shateeb, Hussain (Saudi Aramco)
Abstract We are developing new classes of barcoded advanced tracers, which, compared to present commercial offerings, can be optically detected in an automated fashion. The eventual goal for the advanced tracers is to deploy cost-effective, ubiquitous, long-term, and full-field tracer tests in supporting large-scale waterflooding optimization for improved oil recovery. In this paper, we compare model predictions to breakthrough data from two field tests of advanced tracers in a pilot during water alternating gas (WAG) cycles, where gas tracer tests have recently been performed as well. Two advanced tracer injections were performed at the test site. For the first injection, only a dipicolinic acid based advanced tracer (DPA) was injected. For the second injection, DPA and a phenanthroline- based advanced tracer, 4,7-bis(sulfonatophenyl)-1,10-phenanthroline-2,9-dicarboxylic acid (BSPPDA), was injected in conjunction with a commercially available fluorobenzoic acid-based tracer (FBA) to benchmark their performance. Produced water samples were collected weekly for tracer analysis. Both newly developed 2D-high performance liquid chromatography/time-resolved fluorescence optical detection method (2D-HPLC/TRF) and liquid chromatography-mass spectrometry (LC-MS) were used to construct the breakthrough curves for the advanced tracers. In parallel, gas chromatography-mass spectrometry (GC-MS) was used to detect FBA tracer. Gas tracer tests have been performed on the same field. Since DPA, BSPPDA and FBA tracers were water tracers as designed, they were expected to appear in between gas tracer breakthroughs, and we observed exactly that for BSPPDA and FBA. Unexpectedly, the DPA predominantly appeared along with gas tracer breakthroughs, suggesting its favorable compatibility with the gas phase. We suspect the presence of some gas components rendered the medium more acidic, which likely protonates DPA molecules, thereby alters its hydrophilicity. A wealth of information could be gathered from the field tests. First, all tracers survived not only the harsh reservoir conditions but also the irregular WAG injections. Their successful detection from the producers suggested robustness of these materials for reservoir applications. Second, the breakthrough curves of the BSPPDA tracers using optical detection method were very similar to those of FBA tracers detected by GC-MS, substantiating the competency of our in-house materials and detection methods to the present commercial offerings. Finally, even though DPA has passed prior lab tests as a good water tracer, its high solubility to gas phase warrants further investigation. This paper summarizes key results from two field trials of the novel barcoded advanced tracers, of which both the tracer materials and detection methods are new to the industry. Importantly, the two co- injected advanced tracers showed opposite correlations to the gas tracers, highlighting the complex physicochemical interactions in reservoir conditions. Nevertheless, the information collected from the field trials is invaluable in enabling further design and utilization of the advanced tracers in fulfilling their wonderful promises.
Summary Seawater breakthrough percentage monitoring is critical for offshore oil reservoirs because seawater fraction is an important parameter for estimating the severity of many flow assurance issues caused by seawater injection and further developing effective strategies to mitigate the impact of those issues on production. The validation of using natural ions as a tracer to calculate the seawater fraction was investigated systematically by studying the natural chemical composition evolution in porous media using coreflood tests and static bottle tests. The applicable range of ions was discussed based on the interaction between ion and rock. The barium sulfate reactive model was improved by integrating interaction between ions and rock as well as fluid flow effect. The results indicate that chloride and sodium interact with rock, but the influence of the interaction can be minimized to a negligible level because of the high concentrations of chloride and sodium. Thus, chloride and sodium can be used as conservative tracers during the seawater flooding process. However, adsorption/desorption may have a large influence on chloride and sodium concentrations under the scenario that both injection water and formation water have low chloride and sodium content. Bromide shows negligible interaction with rock even at low concentrations and can be regarded as being conservative. The application of a barium and sulfate reaction model in coreflood tests does not work as well as in bottle tests because fluid flow in porous media and ion interaction with rock is not taken into account. Although sulfate and barium adsorption on clay is small, it should not be neglected. The barium sulfate reaction model was improved based on the simulation of ion transport in porous media. Cations (magnesium, calcium, and potassium) are involved in the complicated cation-exchange process, which causes large deviation. Therefore, magnesium, calcium, and potassium are not recommended to calculate seawater fraction. Boron, which exists as anions in formation water and is used as a conservative tracer, has significant interactions with core matrix, and using boron in an ion tracking method directly can significantly underestimate the seawater fraction. The results give guidelines on selecting suitable ions as tracers to determine seawater breakthrough percentages under different production scenarios.