Masini, Cristian (Petroleum Development Oman) | Al Shuaili, Khalid Said (Petroleum Development Oman) | Kuzmichev, Dmitry (Leap Energy) | Mironenko, Yulia (Leap Energy) | Majidaie, Saeed (Formerly with Leap Energy) | Buoy, Rina (Formerly with Leap Energy) | Alessio, Laurent Didier (Leap Energy) | Malakhov, Denis (Target Oilfield Services) | Ryzhov, Sergey (Formerly with Target Oilfield Services) | Postuma, Willem (Target Oilfield Services)
Unlocking the potential of existing assets and efficient production optimisation can be a challenging task from resource and technical execution point of view when using traditional static and dynamic modelling workflows making decision-making process inefficient and less robust.
A set of modern techniques in data processing and artificial intelligence could change the pattern of decision-making process for oil and gas fields within next few years. This paper presents an innovative workflow based on predictive analytics methods and machine learning to establish a new approach for assets management and fields’ optimisation. Based on the merge between classical reservoir engineering and Locate-the-Remaining-Oil (LTRO) techniques combined with smart data science and innovative deep learning algorithms this workflow proves that turnaround time for subsurface assets evaluation and optimisation could shrink from many months into a few weeks.
In this paper we present the results of the study, conducted on the Z field located in the South of Oman, using an efficient ROCM (Remaining Oil Compliant Mapping) workflow within an advanced LTRO software package. The goal of the study was to perform an evaluation of quantified and risked remaining oil for infill drilling and establish a field redevelopment strategy.
The resource in place assessment is complemented with production forecast. A neural network engine coupled with ROCM allowed to test various infill scenarios using predictive analytics. Results of the study have been validated against 3D reservoir simulation, whereby a dynamic sector model was created and history matched.
Z asset has a number of challenges starting from the fact that for the last 25 years the field has been developed by horizontal producers. The geological challenges are related to the high degree of reservoir heterogeneity which, combined with high oil viscosity, leads to water fingering effects. These aspects are making dynamic modelling challenging and time consuming.
In this paper, we describe in details the workflow elements to determine risked remaining oil saturation distribution, along with the results of ROCM and a full-field forecast for infill development scenarios by using neural network predictive analytics validated against drilled infills performance.
Africa (Sub-Sahara) Bowleven's Moambe exploration well on the Bomono Permit onshore Cameroon has encountered hydrocarbons. The well was drilled to a planned total depth of 5,803 ft and made its discovery in Paleocene-aged (Tertiary) target reservoir intervals. Moambe is the second in a two-well exploration program on the permit. The first well, Zingana, also discovered hydrocarbons. The Moambe well will be tested before further testing takes place at Zingana. Bowleven holds 100% interest in the permit. Shell Nigeria Exploration and Production has begun production at the Bonga Phase 3 project, an expansion of the deepwater Bonga project in Nigeria. Peak production from the expansion is expected to be 50,000 BOEPD, which will be shipped by pipelines to the Bonga floating production, storage, and offloading facility.
SPE, through its Energy4me programme, will present a free one-day energy education workshop for science teachers (grades 8–12). A variety of free instructional materials will be available to take back to the classroom. Educators will receive comprehensive, objective information about the scientific concepts of energy and its importance while discovering the world of oil and natural gas exploration and production. Energy4me is an energy educational public outreach programme that highlights how energy works in our everyday lives and promote information about career opportunities in petroleum engineering and the upstream professions. SPE’s Energy4me programme values the role teachers and energy professionals play in educating young people about the importance of energy.
Objectives/Scope: The continuous drive by the E&P industry to deliver additional value and performance improvements in unconventional reservoirs has created the need for innovative advances in technology to meet evolving challenges. Jweda et al. (2017) and Liu et al. (2017) developed a novel time-lapse geochemistry technology calibrated to core extracted oils to cost effectively ascertain vertical drainage, which is among the most critical parameters used in determining optimal field development strategies. Aqueous geochemistry, well-established in academic and environmental investigations, is another technology that can be used in conjunction with time-lapse hydrocarbon geochemistry to evaluate drainage behavior, vertical connectivity between stacked wells and to ascertain the efficacy of different stimulation designs. Methods/Procedures/Process: More than 300 produced water samples from approximately 60 different Eagle Ford wells have been collected across ConocoPhillips’ Eagle Ford acreage. Sampling campaigns have included collecting several long-term time-series and baseline samples from individual wells across the field. The analytical program consists of a suite of total ion chemistry (cations and anions), salinity, alkalinity, and isotopic geochemistry (δ18O, δD, 87Sr/86Sr, δ11B). Results/Observations/Conclusions: Produced waters, contain a robust arsenal of geochemical signals that can be analyzed to understand the provenance(s) and change(s) in composition with time of these produced waters. A combination of interpretative and multivariate statistical tools were used to gain a deeper understanding of water-rock interactions and mixing/diffusion processes in the subsurface. Stimulation water was differentiated from in-situ formation water, and the evolution of that process was tracked over time. Time-series water analyses were also used to evaluate differences between completion designs, determine the vertical drainage and/or communication between wells, and ultimately understand the drained rock volume through time. Applications/Significance/Novelty: We clearly demonstrate that produced waters are mixtures of stimulation and formation water and that long-term geochemical signals from different layers within the Eagle Ford can be differentiated using aqueous geochemistry. Furthermore, we show that the formation waters vary vertically, coincident with hydrocarbon indicators (oil biomarkers and gas isotopes). To our knowledge, this is among the first published studies of aqueous geochemical behavior of produced waters in the Eagle Ford and the first to establish that intra-formational waters can be discerned, which is particularly novel and important for evaluating completion designs and strategies within a stacked development.
Multistage hydraulically fractured horizontal well completions have come a long way in the last two decades. Much of this advancement can be attributed to the shale gas revolution, from which numerous transformational tools, techniques, and concepts have led to the efficient development of ultralow-permeability resources on a massive scale. Part of this achievement has been through a widespread trial and error approach, with the higher risk/failure tolerance that is a trademark of the statistical nature of the North American unconventional resource business. However, careful consideration must be taken not to blindly apply these techniques in more permeable tight gas formations, which often cover an extensive range of permeability. Inappropriate application can compromise the effectiveness of the hydraulic fracture treatment and impair long-term well productivity.
Khazzan is a tight to low-end conventional gas field in the Sultanate of Oman, with low porosity and permeability in comparison to conventional formations. The target formations comprise extremely hard, highly stressed rocks at high temperature. The development strategy included vertical wells with massive hydraulic fracture treatments and multistage fractured horizontal wells. The former has been largely successful in the higher-permeability areas, and the economic transition from vertical to horizontal well development, based on rock quality, is continuously evolving. Compared to the rapid learning curve achieved through the more than 80 vertical wells drilled to date, fewer horizontal wells have been drilled, and, as a result, the understanding is still relatively immature.
The paper outlines the technical and operational journey experienced in horizontal wells, to prepare the wellbore and ensure a suitable frac/well connection for successful fracturing and well testing. The paper will describe how the intervention tools and practices have varied between the Barik and Amin formations; depending upon rock quality, frac treatment type, drive to maximize operational efficiency and availability of local resources. The differential application of these techniques, that result in measurable under-flush versus in contrast to the typical North American unconventional practice of defined but limited overflush (e.g., pump-down plug-and-perf will be described). Justification for these different approaches in two very different formations will be demonstrated, including supporting evidence of their relative value.
The obstacles that have been faced, overcome and are still ongoing with this campaign highlight the importance of several critical factors: including multi-disciplinary integration and planning, wellbore construction impacts, contractor performance and tool reliability. Although practices for shale and very low permeability sands are well documented, this paper provides a suite of case histories and operational results for horizontal well intervention techniques used in high-pressure and high-temperature sandstones that are in the very specialized transition zone between conventional and unconventional.
Reliable estimation of geomechanical properties (i.e., Young's modulus and Poisson's ratio) of shale can provide important constraints to guide production by identifying sweet spots and locations for effective hydraulic fracturing. Amplitude Variation with Offset (AVO) inversion may make important contributions to such tasks, since it is an effective method to estimate elastic parameters of target layers. However, to estimate geomechanical and even elastic properties of shale from AVO inversion is not a trivial task, since organic-rich shale formations are often anisotropic. Our objective is to apply a nonlinear AVO inversion using the exact Zoeppritz solutions instead of its linear approximation. It allows estimation of seismic anisotropy and furthermore estimates of anisotropy of geomechanical properties. We first reformulate the exact Zoeppritz equations for reflection coefficients in terms of four parameters (one ratio of background P-wave and S-wave velocities, and three contrasts of P-wave and S-wave velocities, and density). An adjoint state technique is applied to compute the gradient of reflection amplitudes modeled by the parameters. This allows the nonlinear AVO inversion possible. We then propose a workflow to estimate seismic anisotropy and geomechanical properties of organic-rich shale. It is based on analyses of results from the AVO inversion. The anisotropy of the model shale is related to the kerogen volume fraction values using measured well logs and laboratory data for various shale formations. By applying inversion tests, we determine behaviors of the AVO inversion solutions developed for isotropic media when the target shale formation instead has seismic anisotropy related to organic content. These tests show that the inversion accurately determines horizontal P-wave and S-wave velocities and underestimates density when a far angle range is applied with input data. When the angle range is small, the inversion can obtain reliable vertical velocities, and correct density. Therefore, seismic anisotropy of the model can be estimated by comparing these inverted horizontal and vertical velocities. In addition, geomechanical properties of the model are also reliably determined in both horizontal and vertical directions. In contrast to most conventional AVO inversions based on linear approximations of the Zoeppritz equations, the proposed Zoeppritz AVO inversion is not limited by assumptions of weak contrasts and seismic isotropy. This allows better estimations of elastic and geomechanical properties and their anisotropy for unconventional shale play which are highly anisotropic and often surrounded by hard layers to generate strong contrasts. Given reliable inference of geomechanical properties from the AVO inversion, the results can directly impact to quantify fracability of unconventional play. Consequently, the workflow for nonlinear AVO inversion contributes to optimization of well placement, stimulated reservoir volume (SRV), and completion design of unconventional reservoir development.
Process zone stress (PZS) has been found to correlate to poor stimulation efficiency and low production. Several models for estimating PZS have been developed by correlating to petrophysical logs (e.g., bulk density (RhoB), porosity (PhiE) and shale volume (Vsh)). Common practice, which does not capture lateral reservoir heterogeneity, uses logs in vertical wells to build a layer-cake model. This study uses geomechanical data acquired while drilling a horizontal well to build a calibrated petrophysical interpretation of bulk density, porosity and shale volume in order to estimate PZS. This workflow results in a stage-by-stage prediction of possible operational issues, which can improve operational efficiency and maximize the effectively-stimulated lateral length.
Geomechanical data were acquired in both a pilot and horizontal well in the Lower Lance Pool (LLP), Green River Basin, Wyoming. The geomechanical properties (Young's Modulus, Poisson's Ratio and VTI anisotropy) were calibrated with wireline in the pilot to calculate RhoB, PhiE, and Vsh. The calibrated petrophysical model was then applied to the mechanical data in the lateral wellbore, providing the inputs necessary for the PZS calculation.
Three PZS models were built in a 3D multi-well finite difference simulator using each of the three petrophysical inputs. Scalars for the models were calibrated to offset DFIT data. The resulting models were compared to determine the optimal model. Pre-stimulation instantaneous shut in pressures (ISIP) was evaluated in the horizontal well for each stage. High pre-job ISIP values are an indicator of stages that may be difficult to break down because of the apparent increase in stress associated with initiating and propagating the fracture. The ISIP analyses were compared to the prediction based on the synthetic PZS models to validate the result.
The three PZS models were evaluated for consistent, predictive behavior in the LLP. Results indicate that the RhoB and PhiE models were more consistent than the Vsh model. Additionally, the RhoB model benefits from more widely available calibration to offset triple-combo data, allowing it to be used with greater confidence throughout the basin.
A predicted ISIP was calculated (closure pressure + PZS) and compared to the pre-job ISIP analyses. The model predicted an average ISIP around 2% or less across the lateral. In contrast, a layer-cake model using the pilot data workflow predicted ISIP around 9% of actual. This variability may be caused by lateral changes in reservoir quality which the layer-cake model does not account for.
This workflow provides a calibrated method for incorporating PZS into a horizontal well using geomechanical data. The application accounts for the reservoir's heterogeneity, where the layer-cake approach to applying PZS is insufficient. The integration of the petro-mechanical and completion methodologies provides a unique opportunity to optimize completions in horizontal wells.
Fu, Qinwen (University of Kansas) | Cudjoe, Sherifa (University of Kansas) | Barati, Reza (University of Kansas) | Tsau, Jyun-Syung (University of Kansas) | Li, Xiaoli (University of Kansas) | Peltier, Karen (University of Kansas - Tertiary Oil Recovery Project (TORP)) | Mohrbacher, David (Chesapeake Energy) | Baldwin, Amanda (Chesapeake Energy) | Nicoud, Brian (Chesapeake Energy) | Bradford, Kyle (Chesapeake Energy)
Fracture complexity, phase behavior, lithological variations and diffusion of gas from the fracture into the oil-saturated nano-pores are the main contributing factors in oil recovery using gas huff-n-puff injection. Limited research was conducted to define diffusion coefficients coupled with the rock tortuosity. The objective of this work is to conduct a comprehensive experimental and simulation study on Lower Eagle Ford rock samples to measure the diffusion coefficients for different injection cycles in three representative litho-facies.
Three representative rock samples were selected based on their differences in petrophysical properties. Saturated volumes were measured using a low-field nuclear magnetic resonance (NMR) measurement and confirmed with material balance for cores saturated at reservoir conditions. Pressure was recorded during a one-day diffusion process before it was dropped linearly at the end of each cycle for production, and the effluent oil and gas composition were measured. NMR measurement was repeated at the end. A compositional simulation model was set up using tortuosity values from FIB-SEM analysis to simulate the experimental diffusion and production. History matching on pressure and production results was conducted and diffusion coefficients were estimated for one representative sample.
Pressure profiles vary significantly between different cycles due to different effective diffusion coefficients. This may be caused by invasion of the gaseous phase into a new section of the pore network during each cycle. Diffusion coefficients, represented by pressure drop during the soaking time, vary across different litho-facies and for different cycles. For the produced oil, the concentration of lighter oil components declined from the first to the last cycle of gas injection while the concentration of the intermediate and heavier components increased.
Gas huff-n-puff injection into shale oil reservoirs is being investigated from the point of view of diffusion and variations in rock properties for the first time and measurements were validated using numerical simulation. The huff-n-puff experiments show favorable results, using constant volume diffusion cell with locally produced hydrocarbon gas and stock-tank oil, the recovery factors for samples A, B, and C are 57.5%, 56.7%, and 51.7%, respectively. The history matched oil diffusion coefficients are in the range of ten to the power of negative seven, and are in close relation with the remaining oil composition.
A workflow is presented which places far greater emphasis on formation lithology than is usually employed during pore pressure and geomechanical studies. Advanced classification techniques are linked with conventional pore pressure prediction and geomechanical modelling methods to implement the new workflow. The lithological classifications which are developed permit more robust predictions by facilitating the constraint of pore pressure and geomechanical results to available well data. Lithological assignments are developed from well logs using a Bayesian-based multivariate clustering analysis technique which yields a probabilistic Electroclass at each depth along the wellbore. The probabilistic results are analysed with an Expert System that automatically assigns a Lithology to the Electroclass at each depth. The Expert System can be modified for different regions and adjusted (and overruled) by an experienced analyst. The resulting multivariate model, with probabilistic lithological assignment, is used to QC, and if necessary predict, well log curves in missing intervals along the wellbore. Thus, interval velocities across the complete well profile from surface to total depth can be established from well log sonic data. These lithology-dependent velocities are then used to develop pore pressure predictions using an effective stress method in which the governing parameters are themselves lithologically dependent. Likewise, geomechanical properties such as Poisson's Ratio, Young's Modulus, Brittleness Index, and the minimum horizontal stress are calculated using Lithology-dependent parameters. An example is presented for an onshore US unconventional formation in which multiple wells are used to develop a robust lithological classification. The developed lithology then controls the wireline log curve predictions and ultimately the pore pressure and geomechanical predictions in selected wells. The impact of different lithologies on pore pressure and geomechanical estimates can be clearly seen and the impact of parameter setting ascertained for each. It is concluded that predictions of pore pressure and geomechanical properties are considerably enhanced by the far better understanding and consistent inclusion of lithology.
You, Junyu (Petoleum Recovery Research Center) | Ampomah, William (Petoleum Recovery Research Center) | Kutsienyo, Eusebius Junior (Petoleum Recovery Research Center) | Sun, Qian (Petoleum Recovery Research Center) | Balch, Robert Scott (Petoleum Recovery Research Center) | Aggrey, Wilberforce Nkrumah (KNUST) | Cather, Martha (Petoleum Recovery Research Center)
This paper presents an optimization methodology on field-scale numerical compositional simulations of CO2 storage and production performance in the Pennsylvanian Upper Morrow sandstone reservoir in the Farnsworth Unit (FWU), Ochiltree County, Texas. This work develops an improved framework that combines hybridized machine learning algorithms for reduced order modeling and optimization techniques to co-optimize field performance and CO2 storage.
The model's framework incorporates geological, geophysical, and engineering data. We calibrated the model with the performance history of an active CO2 flood data to attain a successful history matched model. Uncertain parameters such as reservoir rock properties and relative permeability exponents were adjusted to incorporate potential changes in wettability in our history matched model.
To optimize the objective function which incorporates parameters such as oil recovery factor, CO2 storage and net present value, a proxy model was generated with hybridized multi-layer and radial basis function (RBF) Neural Network methods. To obtain a reliable and robust proxy, the proxy underwent a series of training and calibration runs, an iterative process, until the proxy model reached the specified validation criteria. Once an accepted proxy was realized, hybrid evolutionary and machine learning optimization algorithms were utilized to attain an optimum solution for pre-defined objective function. The uncertain variables and/or control variables used for the optimization study included, gas oil ratio, water alternating gas (WAG) cycle, production rates, bottom hole pressure of producers and injectors. CO2 purchased volume, and recycled gas volume in addition to placement of new infill wells were also considered in the modelling process.
The results from the sensitivity analysis reflect impacts of the control variables on the optimum results. The predictive study suggests that it is possible to develop a robust machine learning optimization algorithm that is reliable for optimizing a developmental strategy to maximize both oil production and storage of CO2 in aqueous-gaseous-mineral phases within the FWU.