Reservoir modeling and the derived fluid production over time curves are a key part of the workflows associated with major capital project decisions. These models may be very complex and use a variety of geological constraints in an effort to develop the porosity, permeability, and saturation distributions used in dynamic models (with or without upscaling). Over time and partially in response to increased computing capability as well as the need for more realistically heterogeneous models, model size as measured by number of model cells and model complexity has increased but model-derived production forecasts remain optimistic. This paper, one of a series that now stretches back over a decade, addresses a number of modeling issues with the goal of (1) better understanding how modeling workflows may contribute to forecast optimism and (2) what reservoir modelers, both geologists and engineers, may do to reduce forecast optimism derived from their subsurface models by improved understanding of how model parameters such as grid size, number of grid cells, semivariogram parameters (e.g. the range), and number of geological/stratigraphic "control" surfaces used to constrain models. Adequate modeling of reservoir heterogeneity appears to require very to extremely large models (e.g. large number of small cells). Many of the parameters used to "control" heterogeneity including the semivariogram range parameter, the number of "detailed" stratigraphic layers, and the number of rock/facies "containers" or model regions appears to have only a small impact on forecast recovery.
In order to get a full petrophysical evaluation from log-based traditional techniques in every location, the formation density is needed in wire-line log measurements; otherwise, with a limited amount of information in terms of porosity values, the reservoir characterization has more uncertainty. That is, the case study of the giant Bachaquero-02 reservoir, there is a lack of Rhob data in the spatial data sets that prevent a good assessment of the storage capacity in the petrophysical model and thus wrong original oil in place estimation. This paper, therefore, presents a solution to this problem; this work develops a methodology for predicting formation density values which establish a link between probabilistic interpretations from multi-mineral solution and deterministic predictions from multiple linear regression with the main objective of seeking a mathematical expression which describes the best fit for the Bachaquero Member and Laguna Member in each location. The manner of estimating formation density can vary according to the available data in well logs, as a first step, this technique uses classic lithology indicators from well logging such as gamma ray, spontaneous potential and resistivity index to calculate the most probable minerals in the rock with the purpose of assessing a probabilistic approach, the second stage is to create a prediction model with surrounding wells, the input data, which is the probabilistic outcome and measured logs, it is trained using a'least squares' regression routine that will find the best fit in the data for bulk density reckoning. A reliable formation density profile according to the lithology of the reservoir was obtained for each well. The model shows more than 0.9 of correlation coefficients between the density measured by wire-line services and the new bulk density reproduced in this method. Particularly, the Bachaquero-02 reservoir has a notorious heterogeneity along the stratigraphic column; the Bachaquero Member has different depositional environment and rock properties in comparison with Laguna Member which has poor quality reservoir rock. This workflow has the ability to incorporate reservoir heterogeneities in the probabilistic module without a problem. 2 SPE-191163-MS
According to EIA (
The complete evaluation methodology has 4 phases: 1) petrophysical evaluation, that includes multimineral evaluation, porosity estimation and calibration with mineralogical analysis; 2) TOC content evaluation, that includes TOC content estimation, using 3 methods: density logs
La Luna Formation and La Grita Member of Capacho Formation are mainly composed by carbonatic rocks, with high content of calcite (above 75%) and low content of clay minerals. In both units, the estimation of TOC content varies from 0.50 to 9%. Mechanical properties show moderate values of Poisson's ratio (0.20 to 0.32), high values of Young's modulus (0.80 to 9.60x 106 psi) and UCS (6.20 to 31.00x 106 psi). In the Cretaceous sequence, the state of stress changes according to geographic location in the basin, from normal in northwest region and central lake region, to transcurrent and reverse in southeast region. The brittleness index estimated for different methods varies from 0.54 to 0.85, which indicate that both units may be classify as brittle.
The integration of geomechanical and petrophysical analysis allowed identifying prospective intervals in both units, with thickness between 20 to 100 ft. Therefore, the study indicates that both units show very good conditions for horizontal drilling and hydraulic fracturing. Moreover, the comparison of various estimation methods of TOC content and brittleness index allowed to observe the uncertainty presented by these parameters in analysis of shale plays.
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.
The EoceneFrac area corresponds to a subsoil extension of approximately 230 Km2, located northeast of Lake Maracaibo in the Lagunillas area, where Informal Members B-2-X and B-3-X have been defined as The main oil-producing sands of the Misoa Formation of the Eocene Age, classifying the B-2-X-68 deposit as the second at the western level in crude oil reserves and object of this study. The EoceneFrac reservoir is 24 ° API hydrocarbon and this reservoir is currently the second largest reservoir in the western region. Work on this site began in 1927 and is noted for the fact that it has to be fractured due to its low permeabilities, despite being a shallow production zone. The first fracture occurred in 1959 at the well Years later was the discoverer.
It has a significant consolidation, which aggravates the problem of the low fluidity of the hydrocarbons to the intermediations of the well, the deposit currently has forty-nine (49) wells of which are in different states being active sixteen (16), inactive six (6), abandoned seven (7), three (3) waiting for abandonment and finally seventeen (17) waiting for reconditioning works for the date of January 13, 2013, being the main problem affecting the production of these wells the low mobility.
A Geomechanical study focused on optimizing the fracture designs that arose due to the failed behaviors that had been previously carried out in the B2-X-68 deposit, ceased to function shortly after being made, it is noteworthy that they were found Important parameters of rock and proppant resistance that have a direct impact on collapse of the rock, as well as geopresiones that were not taken into account for initial designs.
Successfully implementing polymer flooding and maximizing benefits requires selecting best options of variables such as polymer concentration and slug, and number and location of new wells. Option-decisions combined generate thousands of scenarios. Therefore, even using smart algorithm optimizers to efficiently find the maximum of a business objective mathematical function can be a very time-consuming process.
The objective of this article is to demonstrate a methodology to improve the chances of finding the maximum net present value (NPV) solution for planning an offshore polymer-flooding; this includes finding, for example, the minimum injection volume to more easily offshore operations.
The reservoir and economy models included here were automatically coupled with software that encloses a smart numerical algorithm for searching complex maximum/minimum functions. The options of the previously mentioned decision variables were selected to maximize the NPV of the inverted five-spot polymer-flooding project under constrained rig availability. The process was conducted in three stages: Stage 1: potential value estimation Stage 2: narrowing options through deterministic numerical simulation Stage 3: A) numerical optimization of all decision variable options except the drilling sequence; B) numerical optimization of the drilling sequence
Stage 1: potential value estimation
Stage 2: narrowing options through deterministic numerical simulation
Stage 3: A) numerical optimization of all decision variable options except the drilling sequence; B) numerical optimization of the drilling sequence
A total of 379 scenarios were numerically forecasted in just a few months. The best scenario showed three times the NPV of the nonflooding case. Compared to the reference water-flooding scenario (i.e., all the same options but with the fluid injected), the NPV was 1.3 times greater, the water-oil ratio (WOR) was 0.45 times lower, and Np was 1.25 times greater. Unobvious scenarios, such as reducing the yearly drilling rig availability but extending drilling by four years, were revealed. A comparison of the working time for Stage 2 with Stages 3A and 3B showed that the numerical optimization is six times faster per scenario generated.
This study demonstrates that the use of numerical algorithms of polymer flooding yields a significant incremental value over traditional deterministic simulations in a much shorter time frame and with fewer costs compared to previous steps related to building a reservoir model. It is expected to be applicable to all types of enhanced oil recovery (EOR) processes.
Ugueto C., Gustavo A. (Shell Exploration and Production) | Huckabee, Paul T. (Shell Exploration and Production) | Molenaar, Mathieu M. (Shell Exploration and Production) | Wyker, Brendan (Shell Exploration and Production) | Somanchi, Kiran (Shell Exploration and Production)
It is now well established that the production from horizontal wells completed via hydraulic fracture stimulations (fracs) is highly variable along the length of the wellbore. In addition to subsurface conditions, elements of the completion design, such as fluid volume, proppant tonnage, rate, stage length, the number of perforation clusters and their spacing, influence the performance of individual stimulated intervals and wells. Information about completion efficiency can be obtained using Fiber Optic (FO) diagnostics. Distributed Temperature Sensing (DTS) and Distributed Acoustic Sensing (DAS) provide great insights into the factors controlling frac construction and performance of each perforation cluster. The integrated analysis of DAS and DTS in horizontal wells completed with multiple perforation clusters per stage indicate that, although most perforation clusters receive fluids during the stimulation, there are significant changes in efficiency during the frac stimulation process that can impact frac connectivity, conductivity and ultimately, their production. This presentation illustrates recent observations about Perforation Cluster Efficiency (PCE) using FO diagnostics and summarizes the results for many wells with Cemented Plug and Perforated completions Limited Entry design (CPnP LE).
The first recorded deliberate attempt to stimulate recovery from an oil reservoir by hydrocarbon gas injection was in the Macksburg field, Washington County, OH, ' long before water injection was used for secondary recovery purposes. For almost 60 years, most secondary recovery projects included some form of immiscible gas injection, and its use continued even after the advent of new methods and materials. In spite of this, it was the late 1940's before serious attempts were made to develop quantitative techniques for describing reservoir performance under gas-injection operations, especially with regard to depleted oil reservoirs. Before then, such efforts were directed primarily toward describing the water displacement process. As a result, techniques used to describe the performance characteristics of immiscible gas injection consist of modifications to methods originally developed for describing performance of water-injection operations, even though there is a fundamental difference in the basic displacement mechanisms of the two fluids.
Early U.S. settlements commonly were located close to salt licks that supplied salt to the population. Often these salt springs were contaminated with petroleum. In the Appalachian Mts.. many saline water springs occurred along the crests of anticlines. ' In 1855 it was found that distillation of petroleum produced a light oil that was similar to coal oil and better than whale oil as an illuminant.' This knowledge spurred the search for saline waters that contained oil.
Once an oil exporter, California now depends on imports for more than 60% of its oil supply. This paper examines the oil production outlook for each of California's major oil sources, including California itself. Oil production trends, published geological and engineering reports, and proposed developments in California's supply area are reviewed to define supply trends, especially for the medium-to-heavy, sour crudes that are processed in California's refineries. Refinery upgrading capacity is already highly developed in California, thus it is assumed that a competitive advantage in heavy, sour crudes will continue, although refining heavy oil releases more carbon dioxide.
About a quarter of California's imports are from Alaska, the rest from foreign sources including Saudi Arabia, Ecuador and Iraq. Before foreign sources became so important, California's refining industry processed California's own crudes and Alaska's North Slope crude. Like those crudes, oil from northern Saudi Arabia, southeast Iraq, and Ecuador is also sour and medium to heavy, ranging from 16 to 35° API and from 2 to more than 3% sulfur by weight. By far the most important sour crude development in California's supply area is Saudi Arabia's 900,000 BOPD Manifa project, originally slated for completion in 2011 but now facing delays. Manifa contains oil that ranges from 26 to 31° API and from 2.8 to 3.7% sulfur. Over the longer term, Alaska will continue to play an important supply role if the Chuckchi and Beaufort Seas live up to expectations.
Middle East production is not increasing, yet oil cargoes from the Middle East have to pass growing Asian markets to reach California. Alaska and Mexico also supply oil to the Pacific Basin, but are facing production declines. The effect of rising Asian demand on Pacific Basin oil markets is already visible, with significant amounts of oil coming to California from Atlantic Basin sources such as Angola, Brazil, and Argentina.
The US West Coast pipeline system is separate from the integrated East Coast, Gulf Coast and Midwest system, so energy security issues for the West Coast may differ from those of the country as a whole. There are policy options that could affect California's oil supply security, including increased oil development in Alaska or offshore California, development of additional oil pipeline outlets on Canada's Pacific Coast or substituting natural gas for oil if possible. All of these policy options are currently the subject of political debate.
Historical Oil Production Trends in California's Supply Area
Historical oil production trends are of interest because, unlike reserve estimates, they are readily verifiable factual information. Another issue with published reserve data is the quality of the supporting information; Alberta produces a detailed annual reserves report, while Saudi Arabia and Iraq publish only national aggregate figures. All of the oil production volumes reported in this section are from the annual production survey of the Oil and Gas Journal or the annual report of the Alaska Division of Oil and Gas and do not include natural gas plant liquids.
Iraq's oil production peaked in 1979 at 3.43 million BOPD. In 2007 it was 2.09 million BOPD, but production levels had been affected by internal instability and were higher in 2008.