Seismic Wave Simulation in Fractured Media

Fractured reservoirs, including unconventional fields, are important in global energy supply, particularly for carbonate source rocks. Fractures can influence subsurface fluid flow and the stress state of a reservoir. The knowledge about the existence of fractures, their spatial distributions, and orientations can help us optimize well productivity and reservoir performance. Seismic detection of subsurface fractures provides important measurements to remotely image field-scale fractures. In developing such technology, forward modeling of the seismic response from fractures in the reservoir provides an important alternate tool for imaging subsurface fractures. In this paper, we implement a seismic modeling algorithm which can simulate 3D wave propagation in an arbitrary background media with imbedded fractures. During modeling, the fractures are added to the background medium by linear slip theory. Examples demonstrated the impacts of fractures on the wave propagation patterns for both PP and PS waves. We also investigate the amplitude versus offset (AVO) effects caused by fractures in a layer media and lay out potential applications of forward modeling in the inversion of fracture parameters and the estimation of fluid contents.

Modified Carbon Dots with Lowered Retention and Improved Colloidal Stability for Application in Harsh Reservoir Condition

Tracer technology has been increasingly used in inter-well tests to investigate reservoir performance, reservoir connectivity and residual oil saturation for providing useful information to improve decision making in reservoir management. Stable nanoparticle tracers with high-sensitive real-time detectability are highly desired, and as one of the nanoparticles tracers, carbon dots (C-dots) have been studied and tested as nano-agent tracer in field trial for reservoir monitoring. In this research, we report a modified method to synthesize fluorescent C-dots and fluorinated, sulfonated or zwitterionic functional groups were incoprtated into the C-dots. The synthesis reaction occurs at hydrothermal conditions with inexpensive starting materials and is readily to scale up for industrial application. Optical properties of the synthesized colloidal C-dots were studied by UV-visible and fluorescence spectroscopies. Colloidal stability was studied by dynamic light scattering (DLS) measurements, and retention of the C-dots in porous medium was evaluated by adsorption experiment with limestone rock. The synthesized C-dots are readily dispersible in freshwater and synthetic brines and exhibit improved colloidal stability in hot brine and lowered retention in reservoir rocks. In comparison with those C-dots reported in literatures, our results suggest that the synthesized C-dots using the modified procedure have excellent fluorescence properties, improved thermal stability, photostability, and water dispersibility, enabling their use as optically detectable nano-agent tracer in oil field application.

Minimizing Carbon Footprint by Smart Sustainable Reservoir Management

Sustainability and reducing carbon footprint has attracted attention in the oil and gas industry to optimize recovery and increase efficiency. The 4th Industrial Revolution has made an enormous impact in the oil and gas industry and on analyzing carbon footprint reduction opportunities. This allows classification of various reservoir operations, installation of permanent sensors and robots on the field, and reduction of overall power consumption. We present an overview of new AI approaches for optimizing reservoir performance while reducing their carbon footprint. We will outline the significant carbon emissions contributors for field operations and how their impact will change throughout the production's lifecycle from a reservoir. Based on this analysis, we will outline via an AI-driven optimization framework areas of improvement to reduce the carbon footprint considering the uncertainty. We analyzed the framework's performance on a synthetic reservoir model with several producing wells, water, and CO2 injecting wells. Beneficial in reducing carbon emissions from the field is the reuse and injection of CO2 for enhancing hydrocarbon production from the reservoir. One hundred different scenarios were then investigated utilizing an innovative autoregressive network model to determine the impact of these components on the overall carbon emission of the field and determine its uncertainty. The conclusions from the analysis were then incorporated into a data-driven optimization routine to minimize carbon footprint while maximizing reservoir performance. The final optimization results of the showcase outlined the ability to reduce the carbon footprint significantly.

Recovery Improvement Using Geological, Technical and Operational Factors of Field Development That Influence the Character of Inflow Profiles in Horizontal Laterals

Currently, it is hard to imagine oil field development management without various surveys, involving resource optimisation for more economical reserves recovery. In this context, the application of new technologies aimed at diagnostics of the state of producing wells opens up multiple opportunities to identify the causes of premature water flooding and reduction in oil production, clarify the geology of the developed deposit, and obtain other useful information in a cost-efficient manner. For several decades now, well logging has been the source of information for field operators on the producing reservoir performance and the composition of fluid flowing across the reservoir through target intervals. However, in the course of time, the industry tends to seek advanced technologies and alternative production logging techniques for well performance diagnostics. Marker-based production logging is just one of the techniques employed to obtain additional data that can be extremely important for prompt decision-making in case of any complicating factors. At the same time, such information requires proper processing and interpretation. The information on how various factors impact the production profile helps develop a set of measures to adjust the oil flow into the well. In this regard, the task above offers a promising outlook for improving the development system efficiency using selective reservoir stimulation, as far as unconventional reservoirs and hard-to-recover reserves are concerned. Therefore, the upstream industry puts a strong focus on further research in this area today.

Impact of Fit-for-Purpose Monitoring on EOR Planning

Challenges in the design of efficient EOR field pilots have been discussed and documented in the industry, particularly when it comes to optimization of monitoring plans for technical and economical perspectives. This paper explores the benefits of pilot planning where the monitoring/control strategies are included in the early stages of the design to reduce risk of measurements ambiguity and ensure good quality pilot results evaluation. It addresses the use of new and existing technology in monitoring by highlighting the advantages and challenges of each alternative including potential pairing of complementary options to achieve the pilot objectives including illustration of the use of continuous and sporadic measurements on the evaluation. The proposed approach starts with a review of reservoir performance, heterogeneity and pilot objectives to ascertain the plausible monitoring technologies/strategies to aid during the pilot de-risking, followed by the identification of adequate novel and mature monitoring options, which are specific to EOR type and measurement nature (permanent, time lapse, etc.). Advantages of incorporating the monitoring strategy as integral part of the pilot design, as well as evaluation of the effectiveness/viability in the presence of uncertainty of the selected monitoring alternatives are discussed providing a reference of suitable/plausible EOR specific technologies. The paper illustrates the importance of selecting monitoring alternatives that feed off each other and the importance of using fit-for-purpose evaluation algorithms and a digitally enabled, structured approach to analyze and democratize pilot results and enable actionable decisions in operations.

New Insights on the Lower Lekhwair Formation offshore Abu Dhabi: Understanding the Key Role of Lithocodium/bacinella Floatstones on Large Scale Reservoir Quality Variations

The Lower Cretaceous Lekhwair Formation is one of the most prolific oil reservoirs in onshore and offshore UAE, yet the available literature on this interval remains limited. Based on a recent study carried out in collaboration with ADNOC Offshore, the present paper provides new insights into the comprehension of the interplay between primary depositional and secondary diagenetic controls on the reservoir performance, which is of crucial importance for the refinement of the static and dynamic models. In offshore Abu Dhabi, the Lower Lekhwair Formation is characterised by an alternation of relatively thick argillaceous (dense zones) and clean limestones (reservoir zones). Reservoir zones consist of basal, low to moderate energy inner ramp deposits, grading upward into thick inner and mid-ramp sediments. Lithocodium/Bacinella is the volumetrically dominant skeletal allochem and can form m-thick, stacked floatstone units. Such Lithocodium/Bacinella-rich floatstones are interpreted to originate from a mid-ramp depositional setting as a result of an increase in the accommodation space. By contrast, the contribution of Lithocodium/Bacinella floatstones is significantly reduced in inner ramp settings where these tend to form cm- to dm-scale, laterally discontinuous interbeds. The combination of sedimentological findings with diagenetic data provided an enhanced understanding of the origin and variations of the reservoir quality across the Lower Lekhwair Formation. In more detail, the best reservoir quality occurs within poorly cemented, Lithocodium/Bacinella-rich floatstones with grain-supported matrices, which favoured the preservation of a macropore-dominated pore system allowing an effective fluid flow. By contrast, the mud-supported textures with only rare and localised occurrence of mm- to cm-scale Lithocodium/Bacinella clumps, present the poorest reservoir quality due to the isolated nature of the macropores and the relatively tight micrite matrix surrounding them. At the large scale, the Lower Lekhwair shows an upward increase in reservoir quality, consistently with the upward increase in abundance and thickness of the Lithocodium/Bacinella-rich floatstones. The integration of depositional features with diagenetic overprint in the Lower Lekhwair Formation shows the fundamental role played by Lithocodium/Bacinella-rich floatstones with grain-supported matrices on the reservoir quality distribution. The impact of the Lithocodium/Bacinella floatstone matrices on the reservoir performance was never investigated before and hence represents an element of innovation and a powerful tool to predict the distribution of the areas hosting the best reservoir properties.

Using New Intervention-less Surveillance Technology to Optimize the Implementation of Waterflood

The value of implementing intervention-less downhole surveillance technology lies in early assessment of field-scale reservoir performance and well deliverability in South Oman's largest waterflood development. Such technology can aid in assessing whether aquifer support by means of (controlled) fracture injection is achievable, which is potentially more valuable than matrix injection to enhance oil production. At the same time HSSE exposure and deferment will be reduced by avoiding well interventions. This paper will share learnings from Distributed Fiber-Optic (FO) Sensing technology. More specifically, this paper will present the case study of field ‘A’, where waterflood is being operated in two methods based on sectors depending on field geological and reservoir properties: ‘Deep’ water injection in the aquifer, under fracture conditions ‘Shallow’ water injection close to the oil-water-contact (OWC), under matrix conditions ‘Deep’ water injection minimizes the risk of early water breakthrough, but it delays the aquifer pressure support which in turn means lower offtake. The ‘Shallow’ water injection (trialed by injecting water 50m below OWC) has a higher risk of water short circuiting, accelerates pressure support and thereby enhances production / well deliverability. Fiber-optic data is part of a decision-based surveillance program, which also included injection / production logging via PLT, step-rate tests, and pressure monitoring. The time-lapse data has illustrated some fracture growth up- and downwards of the perforation interval in most wells but is still contained below the OWC. In some wells, the injection growth is also controlled by the presence of several intra-reservoir shale baffles that are acting as barriers to vertical communication and thereby delaying the injection response while inducing a strong pressure response in nearby producers. The data has helped to further calibrate and validate the model assumptions and will help in optimizing the waterflood development concept for the field. Proactive interventional-less surveillance enables monitoring of the zonal injection conformance, provides advantage of learning reservoir performance and supports agile WRFM operations and decision making. Furthermore, cost competitive and credible technology have made PDO a front runner to keep subsurface risk at as low as reasonably practical levels and boost oil production. This distributed fiber optic sensing technology provided cost-effective, fit-for-purpose, and intervention-less well-and-reservoir surveillance.

Overcoming Production Logging Challenges in Evaluating Extended Reach Horizontal Wells with Advanced Completions

Objective/ Scope Production logging analysis is essential to understand and evaluate reservoir performance throughout the lifetime of an oil well. Data acquisition and analysis is known to be challenging in modern extended reach horizontal wells due to multiple factors such as conveyance difficulties, fluid segregation, debris, or open hole washouts. Advanced compact multiple array production logging tool (APLT) is proposed to minimize the uncertainties related to these challenges. Method, Procedure, and Process The proposed sensor deployment method provides a comprehensive borehole coverage, thus maximizing the amount of subsurface information collected to evaluate the production performance of a horizontal well. Essential measurements are combined on six individual arms. Each arm is independently deployed which guarantees the best borehole coverage in a variety of borehole condition. Robust mechanical arm design minimizes damage, allows tolerance to decentralization, and provides greater confidence in determining the sensor locations. Each arm utilizes two fluid holdup sensors (Resistance, Optical) and one velocity sensor (Micro-Spinner). Co-location of the sensors minimizes the uncertainty related to sensor spacing when compared with previous generation of APLT. Results, Observations, Conclusions The new sensor deployment method and analysis results are discussed showing the added value in barefoot completion as well as advanced ICD completion. The holdup sensors response from previous generation APLT is compared to the advanced tool and how it relates to better borehole coverage. The results also illustrate use of high frequency optical probes for phase holdup determination. In addition, the optical probes are used to confirm bubble point pressure at in situ conditions by confidently detecting the first gas indication in the tubular. The results clearly show how a compact APLT maximizes the borehole coverage in highly deviated and horizontal wells. This is critical in collecting representative data of all segregated fluids which enables more accurate interpretation of the flow profile in the well and better understanding of reservoir performance. Novel / Additive Information The novelty of the new instrument is the ability to maximize the amount of subsurface production logging information collected with low uncertainty and minimum operational risk.