This work presents the carbon dioxide (CO2) storage capacity of the Wolfcamp formation in West Texas. The potential of CO2 for enhanced oil recovery from unconventional liquid reservoirs have been under investigation in recent years. Quantifying the rock ability to store CO2 is necessary for the economic assessment of CO2 EOR, and for the evaluation of carbon sequestration capacity. We measured the porosity, the rock compressibility and the CO2 sorption in sidewall core plugs taken from two wells drilled in the Wolfcamp shale. Computed tomography scanning technology was used to image the samples and investigate the relation between rock density and porosity, and rock density and CO2 sorption.
A gas expansion pycnometer was used for the experiments. To accommodate the challenges associated with extremely tight rocks the equipment was provided with accurate temperature control, and a high resolution gauge with the capability of recording pressure as a function of time. Porosity and compressibility were measured simultaneously using helium. We used different treatments for the rock compressibility and explored its behavior at low pressure. A Langmuir isotherm was used to account for sorption of CO2 on the organic matter of the shale. The volume available for free gas was corrected by incorporating the rock compressibility and the volume of the layer of sorbed CO2 in the analysis of the sorption data.
This study adds to the understanding of the storage capacity of the Wolfcamp shale. We found the porosity to be between 5.94 and 10.30%, the Langmuir volume between 38.77 and 154.51 scf/ton, and the Langmuir pressure from 512.59 to 1384.52 psig. Using CT number as a proxy for total organic content, we observed a linear relation between CT number and sorption capacity. Porosity also showed a linear relation with CT number. Free CO2 storage is the main storage mechanism, at pressures above 2500 psig (for all samples) accounting for more than 80 %. Sorption is a relevant storage mechanism at low reservoir pressure. Neglecting the rock compressibility or the volume of the sorbed layer can lead to wrong estimates of sorption capacity.
The techniques developed in this work provide for an economic and accurate mean of measuring porosity, compressibility, and sorption in tight unconventional core plugs. The use of a non-destructive approach is necessary to characterize core plugs that must remain intact for further testing such as the evaluation of enhanced recovery techniques in unconventional reservoirs. This research provides relevant data for the economic assessment of CO2 EOR in the Wolfcamp and the potential for carbon sequestration. The linear relations we observed for both, porosity and sorption capacity, with CT numbers, are of extreme interest as they can be exploited for faster petrophysical evaluation of unconventional tight rocks.
Water is the most commonly used injection fluid for flooding/energizing oil reservoirs. Despite oil price fluctuations, water use has continued because of its wide availability, relatively low cost, and ease of handling. Decades of research and field application experiences have yielded a sound theoretical approach and practical knowledge of the subject. Nevertheless, water injection deployment and operations can still benefit from optimization. This paper discusses the state-of-the-art use of numerical optimizers based on smart algorithms and stochastic machines that couple subsurface, surface, and economic models.
During planning and operations of waterflooding projects, many decisions are made, such as the number, location, and drilling sequence of new injector and producer wells, total and per well injection rates, well conversion, and fluid withdrawal rates. In addition, each decision variable has multiple options, which combined can generate hundreds or thousands of scenarios, raising the key question of how the optimum scenario can be determined in a timely manner. Furthermore, the optimum scenario selection process should consider uncertainty (e.g., reservoir properties and oil prices) as well as operational constrains.
Based on previous experience, a general workflow was developed and fine-tuned to help identify optimum scenarios. The workflow begins by defining the scenario matrix using available validated history-match models. Models are coupled with an automatic optimizer/stochastic machine. The study cases considered reservoirs with heavy-to-medium oil, injection by pattern and flank, large variations in original oil in place (OOIP), and number of wells for waterflooding implementation and reactivation planning.
Optimization runs typically require hundreds of iterations to approach the maximum or minimum objective business function. Each iteration corresponds to a scenario. To identify the optimal scenario quickly, various strategies were tested: parallel computing and new methodologies of sequential optimization with reduced number of decision variables, initial exploratory runs with a shortened economic horizon time, and stochastic analysis of selected scenarios of the optimization run. All of these strategies proved successful, depending on the specific situation.
The workflow application in three case studies yielded approximately 30% cumulative production and net present value (NPV) increments, with less economic risk than the traditional deterministic simulation approach and reduced water cut up to 40%; compared to base scenarios, Np and NPV increases higher than 200% were obtained. Furthermore, the workflow application generated a large number of scenarios that provided flexibility to modify operations during unexpected events.
Optimizers/stochastic machines were determined to be a valid means to quantitatively estimate the economy and risks and are a fundamental tool for managing waterflooding projects, resulting in better scenarios than the traditional deterministic approach. The approach is also applicable to all types of enhanced oil recovery (EOR) projects.
Meira, L. A. (University of Campinas) | Coelho, G. P. (University of Campinas) | Silva, C. G. (University of Campinas) | Schiozer, D.J. (University of Campinas) | Santos, A. S. (Center for Petroleum Studies - Cepetro)
This paper presents an extension of the RMFinder technique, previously proposed to identify representative models (RMs) within the decision-making process in oil fields. As there are several uncertainties associated with this decision-making process, a large number of scenarios are supposed to be analyzed, so that high-quality production strategies can be defined. Such broad analysis is often unfeasible, so techniques to automatically identify RMs are particularly relevant. The original RMFinder does not consider the individual probability of each RM, which may not be accurate when the risk curves of the problem are estimated. Therefore, a mechanism to calculate the individual probability of each RM was developed here, together with a graphical way to visualize different proposals of RMs. To automatically identify the optimal probability of each RM, this new version of RMFinder minimizes the deviation between the risk curves generated with the selected RMs and the original risk curves of the problem. The graphical approach automatically exhibits, in a single page per solution, the RM dispersion in the scatter plots, the resulting risk curves and the differences between attribute-level distributions. This helps the decision makers to visualize and compare different sets of RMs. The proposed methodology was applied to a small synthetic problem and to three reservoir models based on real-world Brazilian fields: (i) UNISIM-I-D, a benchmark case based on the Namorado field;
Cervantes-Bravo, R. J. (Universidad Nacional de Ingenieria) | Ñaupari-Barzol, H. (Universidad Nacional de Ingenieria) | Palacios-Chun, N. (Universidad Nacional de Ingenieria) | Jimenez-Nieves, E. T. (CORE Energy) | Magnelli, D. (ITBA) | Huerta-Quiñones, V. A. (Savia Peru)
Tight gas reservoir has potential to provide a significant contribution to meet the global energy demand. However, they involve technical and economic challenges for the commercialization that need to be addressed with the multidisciplinary integration of Geoscience, Engineering and Economics. Unconventional resource plays and tight gas reservoir, are generally characterized by lower geologic risk but higher commercial risk. For that reason, a precise understanding of the potential range can lead to the commercial success; this weighs on the economic evaluation process.
We will focus on local tight gas plays that differ in several aspects, especially in terms of the stage of commercial growth. Due to the large number of uncertainties, deterministic economic modeling provided results with low confidence and was considered as merely a scoping indication of commercial potential. Deterministic and single-point solutions are unable to provide a real check for the input assumptions, which typically leads to overly optimistic results. A better solution still needs to be found.
This paper transmits the consistent and systematic process employed in the evaluation of several tight gas plays, all softwares (e.g. Crystal Ball) tested, the vital role of multidisciplinary participation, iterative modeling efforts and conclusions. Thus, the generation of percentiles (P10, P50, and P90) for the economic indicators: NPV, IRR and Payout, through a probabilistic model that takes three scenarios in each input (Capex, Opex, Gas Price and Reserves); can yield to a more precise and sensible in return calculations of investments on an outlook, with the associated risk from a commercial point of view.
This case study was developed on a sectorial block of the Lajas Formation of the Neuquen Basin, with six wells in production (vertical wells 2000 – 2500 m), a GOIS of 129.22 BCF and a current recover factor estimated in 19 %. An optimum number of infill wells will be proposed with the aim to improve the recover factor higher than 35 % with and an incentive price of Gas Plus fixed at 7.5 US$/MMBTU from the National Government. Thus, the learning curve would be reduced and become to an energy source that enable to fulfill the future energy demand to a medium term for Argentina 2020 year, since the development of Vaca Muerta Shale Gas will have a long-term contribution.
Positive results are expected, which will be increased with the addition of each infill well of 4.2 % (5.38 BCF) in the EUR with a yield of investment (NPV/Investment) of 39 %.
Santos, N. (Universidad Industrial de Santander) | Carrillo Moreno, L. F. (Universidad Industrial de Santander) | Carreño Hernandez, J. H. (Universidad Industrial de Santander) | Rodriguez Molina, J. J. (Universidad Industrial de Santander) | Martinez Lopez, R. A. (Universidad Industrial de Santander) | Modelamiento de Procesos Hidrocarburos, G. (Universidad Industrial de Santander)
Formation damage due to calcite deposition is currently an issue in the five sedimentary basins producers of hydrocarbons in Colombia. At this moment, over 100,000 BOPD are in risk due to this kind of damage. A lab-scale correlation is developed which contemplates thermodynamic and hydrodynamic parameters for predicting the Calcium Carbonate formation tendency in Sandstones. An experimental methodology to recreate the continuous deposition of CaCO3 was implemented using Berea sandstones, scalating different production rates and varying the physicochemical composition of the formation water, reproducing accurately the concentrations of the ions Ca++ of Colombian oilfields (consisting currently the biggest issue in this sort of formation damage). The used methodology consisted in a factorial experimental design, which allows the optimal combination of thermodynamic parameters (represented by the Ca++ concentration) and hydrodynamic parameters (represented by injection rates), along a series of rock-fluid interaction experiments which exhibited a permeability impairment of approximately 80%. The correlation was developed using a specialized software. The proposed correlation predicts the permeability impairment with an 80% adjustment of experimental data. This correlation is valid for low permeability values (less than 150 mD), field-scale velocities between 1 and 10 ft/day, and contemplates regular values of Ca++ ions concentration for Colombian oilfields. Furthermore, the correlation was validated with experimental data obtained at several flow rates (between 1 and 3 cc/min), several temperatures (150 -250°F) and several concentration of Ca++ ions (250-650 ppm). This proposed correlation is the basis to develop a deterministic model, which quantifies the depth, severity and production losses related to this phenomenon.
Thickened CO2 nanofluids are a mean to improve volumetric sweep efficiency and gas production in CO2 EOR projects in contrast CO2 flooding. Alternating injection of plain CO2 with thickened CO2 nanofluid is proposed as an economical alternative using the findings of CO2 viscosity enhancement through nanoparticles in current studies. This was achieved by using CMG GEM simulator and contrasting findings with other WAG and CO2 flooding simulations. The simulation was done on a light oil (40 °API) from a Neuquén Basin reservoir. A sensitivity analysis was done to contrast different type of injection schemes.
As CO2 nanofluids can be tailor made in order to adjust their viscosity (and other properties like asphaltene deposition control) diverse results were observed. Nanofluids improve the volumetric sweet efficiency, and even low viscosity increment increase the overall gas utilization and conformance compared to CO2 flooding. Since there is no face change, the use of CO2 based nanofluids can be a mean to control CO2 EOR projects avoiding injectivity loss problems. It was observed that injection of mere nanofluid (without alternating CO2) is not technically nor economically convenient as it decreases production rates and has an overall lower economic performance than both WAG and CO2 flooding. Nevertheless, alternating nanofluid with plain CO2 enables higher sweep efficiency while lowering the operational costs due to lower volumes of nanofluid utilized. Adding nanofluid to a WAG scheme also shows improvements in EOR performance.
Barredo, S. P. (Instituto Tecnológico de Buenos Aires) | Sosa Massaro, A. (Instituto Tecnológico de Buenos Aires) | Fuenmayor, E. (Instituto Tecnológico de Buenos Aires) | Abalos, R. (Instituto Tecnológico de Buenos Aires) | Stinco, L. P. (Oleumpetra) | Abarzúa, F. (Universidad Nacional de San Juan)
Integrating field and laboratory data is possible if there are strong geologic criteria to relate them. This challenge demands understanding rocks from the fabric and mineralogy up to the architectural elements of rock bodies at a basinal scale. The geological properties of rocks, being them clastic, chemical or biochemical, influence reservoir quality and hydrocarbon producibility, but continental mudrocks/siltstones (shales) are by far more complex because of their depositional nature and highly variable vertical and lateral sedimentary characteristics. Grain size variability and sedimentary structures are common in these rocks. From outcrops, well logs and the source rocks of the Cuyana Basin (Argentina) could be characterized as deposited in lacustrine environments under a strong tectonic and climatic influence. Silty sandstones, limestones, massive and laminated bituminous shales developed in underfilled and balanced to overfilled lakes. They display parallel/inclined/rippled laminations, coarsening/fining upwards patterns, nodules, scour surfaces and pedogenic features. Total organic content may reach 14 % and corresponds to macro and micro floral remains, freshwater invertebrates and kerogen types I and II. These lithofacies are vertically stacked in patterns that can be related to cycles with different mechanical properties. In outcrops and with the help of seismic lines third order depositional sequences representing basin variations in accommodation space were recognized as low accommodation (LAS) to high accommodation (HAS) sequences developed in each of the three rifting stages. Using detailed information about mineralogy and fossil content climate was characterized and fourth order parasequences could be characterized. Fifth order (bedset-rhythms) cycles were interpreted on the basis of outcrops and well logs. Inorganic (especially clays) and organic content, pedogenic fabric, burrows and microfracturing represent weakness planes and as they vary according to these cycles, it was possible to model a mechanical cyclicity along the whole lacustrine column and to analyze their depositional controls. This integrated study has provided relevant data for the understanding of the geological and mechanical properties that will contribute to the optimization of fracture programs.
Silveira, T. M. (Federal University of Rio de Janeiro) | Silva, W. G. (Federal University of Rio de Janeiro) | Couto, P. (Federal University of Rio de Janeiro) | Alves, J. L. (Federal University of Rio de Janeiro)
Pre-salt carbonate reservoirs are known by their huge heterogeneity and their porous system present a challenge regarding reservoir characterization, petrophysical parameters analysis and full understanding of fluid flow dynamics. Besides that, the cost of obtaining rock samples from the reservoir and the destructive nature of most experimental tests increase the interest in develop the concept of Digital Rock Physics (DRP); DRP is based on high resolution imaging and three-dimensional digitizing aiming to investigate and calculate the physical and fluid flow properties of the porous media. In this approach, this work uses X-Ray computed microtomography, digital reconstruction and image processing to achieve the 3D modeling of porous media and estimate petrophysical parameters of Pre-Salt lacustrine carbonate analog samples: coquinas from Morro do Chaves Formation, Northeast Brazil. Experimental data is used to validate the predictions. The results suggest that an important step in the rock digital reconstruction refers to the segmentation process and the high computational cost is a limiting factor to generate the porous media model in three dimensions. Despite this, the estimated physical properties are in good agreement with the previous measured experimental values and the generated 3D model will be widely used in numerical flow simulations in the next steps of this study.
There are many methods and tools for estimating the current water/oil (WOC) or gas/oil contact (GOC) in the reservoir. PLT and RST logs can timely monitor the production of each phase in the well and estimate fluid contacts. Material balance or numerical simulation models allow to estimate or predict the depth fluids contacts. In all cases, these tools involve a large amount of human and financial resources and in most cases their accuracy depends on the time expend to calibrate them.
This work proposes a methodology to determine the current depth of the fluid contacts, using surface measurements of the specific gravity of oil (°API) in wells. The proposed methodology is based on the principle of the compositional variation of the fluid in the reservoir and its effect of the properties of the produced fluids. Two diagnostic plots are proposed: (1) for estimating the current depth of the fluids contact at well level and (2) for predicting water breakthrough time. Some real examples of wells showing the behavior outlined in this paper will be presented to support all presented theories. Finally the proposed methodology and diagnostic plots were applied to a reservoir with proven compositional gradient to validate the proposed work.
This paper presents the workflow and learned lessons during the construction of a fully compositional integrated subsurface/surface model for the Santa Barbara and Pirital fields, which are important oil production units located to the east of Venezuela. In this approach, the numerical reservoir simulation models, wells and surface facilities were coupled in order to obtain production profiles considering both changes in the reservoir conditions and surface restrictions, achieving an assertive planning of asset development.
The applied methodology is based on the construction of more than 150 compositional well models, performing sensitivity analysis to define multiphase flow correlations for vertical pipe and chokes. A network model, which comprises more than 900 Km of lines, 3 main flow stations, and 3 separation levels, was also built in compositional mode honoring line sizes, lengths and elevation changes. Two numerical simulation models represent the most reliable characterization of the main reservoirs. Each model was initialized and ran separately, in order to discard internal inconsistencies. Then, the integration was performed considering the sand face on the wells as the coupling point.
The integrated asset modeling allowed predicting the production behavior of the reservoirs taking into account the constraints of the surface facilities, reducing the uncertainty of forecasts and identifying limitations and bottlenecks at surface level. It was also possible to accurately determine the details of the hydrocarbons streams (NGL) at different pressure stages of the network, which reasonably matched with field data (less than 3% of difference). The result is a versatile tool for the integrated asset management, which allows to sensitize all the elements of the production chain and estimate how each one affect the performance of the asset, discarding the division between departments upstream and downstream and establishing a common management strategy for all disciplines.
The novelty of this work is based on the challenge of building fully compositional coupled models considering giants and complex reservoirs with large surface networks. The proposed methodology and learned lessons will certainly serve as reference for similar future works.