The current scheme for developing shale reservoirs necessitates special considerations while estimating the reserve. While reservoir characteristics lead to an extended infinite acting flow regime, completion schemes could result in a series of linear flows. Therefore, the initial linear flow does not have to be followed by a boundary-dominated flow. Overlooking this observation leads to unphysical Arps’ exponents and overestimations of the Estimated Ultimate Recovery (EUR). We are proposing a workflow to overcome these challenges and honor the inherited uncertainty while using the classic
Determining the potential of shale-gas reservoirs involves an exhaustive process of calculating the volume of total gas, or original gas in place (OGIP). The calculation of total gas relies on calibrating wireline logs to core data, which are considered to be an empirical validation or ‘ground truth’. However, inconsistency in sample preparation and analytical techniques within, and between laboratories creates significant uncertainty in calculating the free- and adsorbed-gas components, which constitute total gas. Here, we present an analytical program performed on samples of core to elucidate the causes of uncertainty in calculation of total gas. The findings of this program are used to propose improved methods of calculating total gas from core.
Free gas calculated from properties, such as porosity and water saturation measured on core, was found to be highly dependent on laboratory analytical protocols. Differences in sample preparation and water extraction methods led to relative differences of 20% in water saturation and 10% in porosity observed between laboratories, leading to differences of 35% in calculations of free gas in place (FGIP).
Adsorbed gas was evaluated using methane adsorption testing to study the changes in Langmuir parameters in samples with a wide variety of water saturations, clay content, and total organic content over a range of temperatures. It was found that the storage capacity of adsorbed gas artificially increased by a factor of two to three when the experimental temperature exceeded the boiling point of water. This increase is related to the expulsion of clay-bound water and subsequent availability of clay surfaces for methane adsorption.
Total gas in place (TGIP) is the sum of free and adsorbed gas volume estimates. The interaction and overlap of pore space between these two volume components are also important to consider. It is proposed to use a simplistic monolayer-based correction of volume of adsorbed gas from the free-gas volume based on a composite pore-size distribution from scanning electron microscopy (SEM) point-counting and nitrogen-adsorption data.
Pressurized sidewall-core samples were acquired at reservoir conditions to measure free- and adsorbed- gas volumes during controlled depressurization under laboratory conditions. This provided a baseline measurement for comparison with calculations from traditional measurements to understand which laboratory protocol and sample preparation technique provided the most robust results.
This study has elucidated methods to reduce the uncertainty in gas-in-place calculations and better understand resource distribution in dry-gas source rocks.
The objective of this paper is to explore the benefits of using the Interactive Epoch-Era Analysis (IEEA) methodology for evaluating architectural changes in a trade space exploration study. In this paper a subsea tieback offshore Brazil will be used as reference case to investigate this premise from a full field development perspective.
An automated concept exploration tool is employed. It applies meta-heuristics to generate different offshore facilities concepts with varying building blocks. The interaction between reservoir behavior and facilities design is accounted for, meaning pressure and temperature losses throughout the system are taken into account in each concept differently. These concepts are ranked in terms of economic performance indicators (NPV, IRR, etc.), and each run with a given set of boundary conditions covers what is called an Epoch. This process is iterated for the whole life of field with a set of different boundary conditions, such as commercial aspects ($/bbl, $/MMBtu, market demand) and/or technological maturity aspects (TRL, novel technological concepts), generating what is called an Era. The whole data set is then evaluated in an interactive platform thru the Humans-In-the-Loop (HIL) process.
Model Based Systems Engineering (MBSE) is being employed successfully in other engineering fields outside the O&G context such as the aerospace and automotive industries. While digital tools have been identified as a potential key contributor to the future of O&G performance enhancement and further cost reductions, that is yet to be shown. This work intends to provide backing for that argument in one of the potential applications during early concept exploration phases by showing that quick high value assessments following an MBSE approach may be carried out, once significant effort has been put into proper development, verification and validation (V&V) of such digital tools.
While integrated models for asset development have long been a subject of interest for O&G operators, the application of Systems Engineering concepts to it has not yet been thoroughly explored. Systems Engineering provides a rigorous and proven method of dealing with complex systems that is highly applicable to offshore field developments. MBSE is the current State of the Art for capital intensive projects such as space exploration spacecrafts and rovers. Learning from these successful use cases and applying these methodologies in the development of digital technologies may provide a new set of tools in the belt of O&G operators Facilities Engineers and alike. The study case presented shows MBSE’s capability of capturing intrinsic non-linearities and specificities of each O&G field/location while ensuring project wide functional requirements are successfully met.
Time does not feature in the equations. However, there are significant advantages if time is incorporated into the analysis. For example: a) identifying if all the wells belong to the same reservoir; b) identifying the effect of external energy sources such as gas or water drive; c) incorporating the contribution of communicating tight reservoirs; d) visualization of the results in pressure-time format. The time-based analysis presented in this paper supplements the conventional methods. It helps reduce the non-uniqueness of the solution. In contrast to the conventional Havlena-Odeh plotting variables, which are complex and non-intuitive, the pressure-time plot and corresponding pressure-history match are much easier for an engineer to comprehend and to evaluate the validity or uniqueness of the results.
Hansen, Mary (McDaniel & Associates Consultants) | Hamm, Brian (McDaniel & Associates Consultants) | Wynveen, Jared (McDaniel & Associates Consultants) | Schlosser, Tyler (McDaniel & Associates Consultants) | Jenkinson, David (McDaniel & Associates Consultants) | Dang, Hoang (McDaniel & Associates Consultants)
Unconventional reservoirs with low permeability shales and siltstones are currently being developed using horizontal wells in multiple layers. As this development technique has become more common, accurately understanding well-to-well communication is increasingly critical. Well positioning, reservoir thickness and well interference effects are important factors in the success of multi-layer development. Traditional well density metrics such as wells per section and lateral well spacing do not account for the multi-layer nature of these plays. This paper introduces readily derived metrics that enable a three-dimensional (3D) quantification of multi-layer well density.
Unlike traditional analysis which considers pad development from a bird’s eye view, this paper considers the vertical cross-section of a pad which enables the 3D drainage to be quantified. The metrics Cross-Sectional Drainage Area (XDA) and Three-Dimensional Proppant Intensity (3DPI) are defined. XDA quantifies the well density relative to the thickness of the reservoir. 3DPI represents completion intensity and reservoir stimulation relative to the cubic volume of gross rock attributed to the multi-layer development. Once introduced, these two metrics are correlated to well and pad level performance. Examples from the Montney Formation in Western Canada and the Bakken Formation in North Dakota, USA are studied in detail.
Ultimate hydrocarbon recovery factors, early time well performance and production profiles are analyzed and compared to the XDA and 3DPI metrics using visual analytics and multivariate machine learning models. In both the Montney and Bakken examples, XDA correlates with well performance and 3DPI correlates with pad hydrocarbon recovery factors.
In the absence of well-developed calibrated geologic and simulation models, empirical approaches such as decline curve analysis (DCA) are normally used for production forecasting and reserve estimation. DCA is computationally more efficient compared to simulation models when the active well base exceeds hundreds of wells. However, the underlying assumption for conventional DCA is no change in well operation settings. Moreover, the common approach for production forecasting consists of manual outlier detection and removal, interpretation of missing measurements and data fitting using different models for each well. Therefore, the process of conventional DCA is subjective due to the lack of a standard workflow for preprocessing and data cleansing. The common practice for doing DCA has three main steps: 1. Finding the most representative period in the history of well, 2. Detecting the initial rate (start point) of forecast, 3. Selecting the type of decline and fitting the appropriate model to data points. The solutions to these problems could vary from engineer to engineer and it can be time consuming to analyze all wells manually. To address these issues, we developed a novel workflow based on stochastic methods for detecting various well interventions including change in artificial lift, pump changes and acid treatment, and for forecasting oil production rate more accurately in the presence of uncertainty. The novelty of the proposed ensemble-based approach is forecasting conditioned on various well interventions. Furthermore, the proposed unsupervised stochastic anomaly detection method will detect various well works (or events) in the case of missing records of time and type of events. In this paper, we designed two experiments to test the proposed workflow for oil production rate forecasting and evaluation of acid treatments.
Purewal, Satinder (Imperial College) | Juárez Toquero, Fidel (National Hydrocarbons Commission of Mexico) | Simón Burgos, Eduardo (National Hydrocarbons Commission of Mexico) | Meneses-Scherrer, Eduardo J. (National Hydrocarbons Commission of Mexico) | Arellano Sánchez, Elaine A. (National Hydrocarbons Commission of Mexico)
A Pilot project was initiated to classify Oil and Gas projects in 19 Blocks in Mexico using the United Nations Framework Classification (UNFC) which has a unique 3-dimensional evaluation structure with three axes: Economics, Environment and Social viability (E axis), Project Feasibility (F axis) and Geological Knowledge (G axis). The main focus was to capture the environmental and social impact on project classification and resources categorization.
The Pilot project was coordinated by the National Hydrocarbons Commission (CNH) with integrated collaboration from the Energy Ministry (SENER), the Agency for Safety, Energy and Environment (ASEA), and the Petroleum Work Group of UNECE. SPE classification system (i.e. PRMS) has been mapped to UNFC. While PRMS covers oil and gas projects only, UNFC covers all resources e.g. oil and gas, minerals, renewables, nuclear, etc.
The E axis uniquely differentiates UNFC from PRMS by its granular capture of social and environmental issues. A systematic approach was adopted with focus on E and F axes for which a matrix and a decision tree (‘flow chart’) were created for an efficient classification of the hydrocarbon volumes. For the G axis, the volume ranges provided by the project operators were considered to be valid. In the selected 19 blocks, there were 75 projects identified. These were located offshore, onshore and included conventional and unconventional projects with varying degrees of environmental and social issues.
This is the first known exercise using UNFC for integrating social and environmental issues into oil and gas projects for hydrocarbon volumes classification and categorization anywhere globally. The outcome shows the differences between the PRMS and UNFC due to social and environmental conditions. Using UNFC for classification and categorization of all energy sources of a country, a potential tool can be created for making energy policy decisions. This may also assist in meeting Sustainable Development Goals- 2030 adopted by most countries including the UN and The World Bank.
Classification using UNFC assists in identifying the key social and environmental drivers which may be impediments to moving the oil and gas volumes categorizations higher up the value chain. Added granularity in the classifications incorporating environmental and social considerations will assist project financial investment decision making through comparative assessment of objectives and priorities of national, regional and local stakeholders. To the authors’ knowledge, this is a unique Pilot project with significant value-add outcomes which can be replicated in other countries.
Booking reserves for unconventional, multi-frac wells is a critical business process, but to be done effectively, often requires significant time investment and multiple interpretation techniques. Although reserves can be estimated quickly with decline curve analysis (DCA) alone, the subjectivity in DCA makes it challenging for evaluators to estimate reserves with appropriate levels of uncertainty and maintain consistency between evaluators. The objective of this paper is to present a fast, systematic, yet rigorous methodology for estimating 1P, 2P and 3P estimated ultimate recoveries (EURs) for new wells. This methodology utilizes regression to correlate easy to obtain, early life indicators of well performance to 2P EURs, which have been estimated from more detailed interpretations. Multiple methodologies are presented for estimating 1P and 3P EURs.
Mature heavy oilfields in the Northern Peruvian Jungle have produced oil for more than 40 years under primary recovery mechanisms (cold methods). As these fields are exploited by a strong water drive assisted with ESPs, total oil production has surpassed more than 1 billion barrels of oil with an average 15% primary recovery factor; ultimate recovery is expected to account for 17% at an economic limit of approximately 98% water cut. According to the
This study explores the development options (technical an economic) to produce heavy oil resources at commercial rates and showcases three optimization scenarios of higher recovery efficiency (additional 5%, 10% and 15% RF) utilizing current technology and sensitizing their economic variables with the main objective of increasing the net present value at the basin level. This is achieved by exploring and validating synergy strategies available in the basin and proposes investment for the Norperuano pipeline revamp to pump light oil/diluent to heavy oilfields (e.g Block 67) and make transportation of volumes currently classified as resources feasible. Lastly, this paper shows the current royalty framework in the Loreto region on a block basis and explores the financing alternatives to foster development and exploration activities in the North Peruvian Jungle heavy oilfields.
The workflow starts with identifying heavy oil development strategies, prioritizing and selecting the most appropriate technologies to optimize production performance and increase recovery efficiency; then, infrastructure options and financing alternatives are carefully reviewed to ensure heavy oil is produced with an appropriate amount of diluent. Finally, royalty and other tax incentives are suggested to ensure a profitable exploitation of heavy oil resources. Typically, primary recovery factors for heavy oilfields range between 10 to 15% with several alternatives for development such as multilateral drilling, steam flooding and HASD which would at least double production rates and increase recovery factors by 10% to 15%. Pilot tests of thermal recovery methods are strongly recommended for some fields in early development stage such as the Bartra field in Block 192 and the Raya and Paiche fields in Blocks 39 and 67 respectively. In order to handle new production rates, modifications to the Norperuano pipeline are proposed; additional in-situ loops and a parallel new pipeline are suggested, not only to ensure diluent/light oil transportation to supply the heavy oilfields, but also to increase transportation capacity of diluted oil to surface storage facilities and to the Refinery Complex in Talara; located on Peru's northern Pacific coast which is currently undergoing an expansion from 65,000 bopd to 95,000 bopd due by November 2020.
Assuming the first two conditions are met (the increase of production rates and recovery factors, and the egress constraint is no longer relevant) the profitability of the project at the basin roll-up level must be tested with a reserves model with inputs such as production rates by block, operating and capital expenditures for the different reserves/production wedges, royalty rates and taxes. The model must be consistent with the development program proposed by the operators in the region and be run at different pricing scenarios to stress-test the break-even value at several levels.
Straight-line analysis (SLA) methods, which are a sub-group of model-based techniques used for rate-transient analysis (RTA), have proven to be immensely useful for evaluating unconventional reservoirs. Transient data can be analyzed using SLA methods to extract reservoir/hydraulic fracture information, while boundary-dominated flow data can be interpreted for fluid-in-place estimates. Because transient flow periods may be extensive, it is also advantageous to evaluate the volume of hydrocarbons-in-place contacted over time to assist with reserves assessment. The new SLA method introduced herein enables reservoir/fracture properties and contacted fluid-in-place (CFIP) to be estimated from the same plot, which is an advantage over traditional SLA techniques.
The new SLA method utilizes the
Validation of the new SLA method for an undersaturated oil case is performed through application to synthetic data generated with an analytical model. Thenew SLA results in estimates of LFP and OFIP that are in excellent agreement with model input (within 2%). Further, the results are consistent with the traditional SLA methods used to estimate LFP(e.g. the square-root of time plot) and OFIP (e.g. the flowing material balance plot).
Practical application of the new SLA method is demonstrated using field cases and experimental data. Field cases studied include online oil production from a multi-fractured horizontal well (MFHW) completed in a tight oil reservoir, and flowback water production from a second MFHW, also completed in a tight oil reservoir. Experimental (gas) data generated using a recently-introduced RTA core analysis technique, were also analyzed using the new SLA method. In all cases, the new SLA method results are in excellent agreement with traditional SLA methods.
The new SLA method introduced herein is an easy-to-apply, fully-analytical RTA technique that can be used for both reservoir/fracture characterization and hydrocarbons-in-place assessment. This method should provide important, complementary information to traditionally-used methods, such as square-root of time and flowing material balance plots, which are commonly used by reservoir engineers for evaluating unconventional reservoirs.