Novel Data-Driven Methodology for Production Allocation Calculation Utilizing Physics-Based Models Coupled and Integrated Within a Digital Framework

Determining the production from each well is crucial for financial and technical purposes. Moreover, this production can be anticipated using several different techniques. This paper describes the procedures to calculate the production allocated to each well in a giant gas-producing field by utilizing physics-based models that are orchestrated in a dynamic digital platform to provide a robust and efficient solution. The cases for this study of allocating gas rates to individual wells were performed using a digital platform as the primary tool utilized to account for the main productional location factors such as well tests and events that are used to estimate actual production volumes. Subsequently, relevant data is extracted, filtered, and loaded into the system in a dynamic interaction with fewer human interventions. The methodology for calculating the production allocated followed these main steps: a) Determine production per well under existing possible measures, b) Determine well contribution factors, c) Distribute actual rates and production according to allocation factors. By using polynomial equations where the inflow performance of the gas wells was verified, the allocation rates were calculated at every desired point of the network. Having an integrated platform proved to be advantageous since it provided a seamless link between different relevant manual and real-time databases and well / network models bringing unique capabilities and benefits. While comparing this integrated and holistic approach versus the previously established one, it was highlighted that production allocation using mainly choke sizes and well test as a sole source for well production can bring significant variations. This creates production mismatches at the well level; therefore, it portrays a misrepresentation of the actual field conditions. Numerous challenges, which are usually faced while calculating the production allocation process, were overcome during the development of this study, such as frequent surface network changes, lack of databases communication, and daily variations on the on/off wells’ status. Furthermore, the data management capabilities of the framework allowed data to be quickly accessible by the users whenever needed allowing them to visualize across the different teams and departments, taking actions when and where required. This standardized methodology provided consistency, reliability, and accuracy, which can be replicated on oil-producing fields and networks; it can be enhanced and scaled in order to incorporate other business processes such as well allowable calculation and voidage monitoring.

The Application of Petroleum Geochemical Methods to Production Allocation of Commingled Fluids

Production allocation from petroleum geochemistry is defined here as the quantitative determination of the amount or portion of a commingled fluid to be assigned to two or more individual fluid sources (e.g., a pipeline, field, reservoir, well) at a particular moment in time, based on the fluid chemistry. It requires: i) knowledge of the original chemical compositions of each of the fluids prior to mixing (referred to here as the "end members"), and ii) that statistically valid differences in their chemistries can be identified. Petroleum geochemical-based methods for production monitoring and allocation are much lower cost than using production logging tools, as there is no additional rig time or extra personnel required at the well site. Additionally, no intervention to the production of hydrocarbons from a well is required and, hence, there is none of the risk entailed in additional operational activity. Geochemical methods are applicable to a wide range of fields, irrespective of pressure, temperature, reservoir quality and reservoir fluid type. The method has been in existence for over 30 years, during which time a number of different analytical methods, data pre-processing and treatment approaches have been applied. This paper summarises these approaches, and provides examples, but also describes a "best practice" which is not a "one size fits all" approach, as is sometimes seen in the literature. A successful production allocation study consists of the following steps: i) Selection of end member samples that contribute to the commingled production fluid; ii) Determination of the differences in chemical composition of the end members through laboratory analysis of the end members (e.g. by WO-GC), replicate analyses of samples and statistical treatment of the data (e.g. PCA); iii) If statistically significant differences exist, laboratory analysis of the end members and commingled fluids with appropriate replicate analyses of samples; iv) Data selection, pre-processing (e.g. selection of ratios or concentrations of components); v) Determination of end member contributions by solving equations (e.g. least squares best fit) and uncertainty estimation (e.g. Monte Carlo or Bootstrap methods). The differences in approach for conventional versus unconventional plays are also discussed.

Full Analytical Modeling Of Intrawell Chemical Tracer Concentration For Robust Production Allocation In Challenging Environments

Conventional downhole dynamic characterization is based on data from standard production logging tool (PLT) strings. Such method is not a feasible option in long horizontal drains, deep water scenarios, subsea clusters, pump-assisted wells and in presence of asphaltenes/solids deposition, mainly due to high costs and risk of tools stuck. In this respect, intrawell chemical tracers (ICT) can represent a valid and unobtrusive monitoring alternative. This paper deals with a new production allocation interpretation model of tracer concentration behavior that can overcome the limitation of standard PLT analyses in challenging environments. ICT are installed along the well completion and are characterized by a unique oil and/or water tracer signature at each selected production interval. Tracer concentration is obtained by dedicated analyses performed for each fluid sample taken at surface during transient production. Next, tracer concentration behavior over time is interpreted, for each producing interval, by means of an ad-hoc one-dimensional partial differential equation model with proper initial and boundary conditions, which describes tracer dispersion and advection profiles in such transient conditions. The full time-dependent analytical solutions are then utilized to obtain the final production allocation. The methodology has been developed and validated using data from a dozen of tracer campaigns. The approach is here presented through a selected case study, where a parallel acquisition of standard PLT and ICT data has been carried out in an offshore well. The aim was to understand if ICT could be used in substitution of the more impacting PLT for the future development wells in the field. At target, the well completion consists of a perforated production liner with tubing. The latter, which is slotted in front of the perforations, includes oil and water tracer systems. The straightforward PLT interpretation shows a clear dynamic well behavior with an oil production profile in line with the expectations from petrophysical information. Then, after a short shut-in period, the ICT-based production allocation has been performed in transient conditions with a very good match with the available outcomes from PLT: in fact, the maximum observed difference in the relative production rates is 5%. In addition, the full analytical solution of the ICT model has been fundamental to completely characterize some complex tracer concentration behaviors over time, corresponding to non-simultaneous activation of the different producing intervals. Given the consistency of the independent PLT and ICT interpretations, the monitoring campaign for the following years has been planned based on ICT only, with consequent impact on risk and cost mitigations. Although the added value of ICT is relatively well known, the successful description of the tracer signals through the full mathematical model is a novel topic and it can open the way for even more advanced applications.

ADDRESSING RESERVOIR HETEROGENEITY BY INTEGRATION OF GEOCHEMISTRY AND PETROPHYSICAL LOGS IN CARBONATE PROSPECTS

Formation evaluation challenges in highly fractured, stacked reservoirs with multiple source rocks and structural complexities that have complicated charging histories are common in the Middle East. Finding additional pay zones, understanding the contribution of individual oils to the overall production, or evaluating the compartmentalization within the reservoir by resolving the heterogeneity of the reservoir rocks are to name but a few. This work tries to understand the challenges posed by the subsurface complexities and attempts to find answers through physical evidence, using both onsite data acquired during drilling and data gathered through organic and inorganic laboratory measurements. Formation evaluation challenges are mostly attributed to formation heterogeneity, which we have aimed to address through the integration of petrophysical and geochemical data within this work. This project encompasses the integration of petrophysical and geochemical analyses of the reservoir rocks. Geochemical data have provided the ability to make maturity, richness, and other character interpretations and will be combined with important petrophysical properties of the carbonate intervals to predict reservoir heterogeneities. These interpretations could support perforation interval selection on subsequent wells in the field through the understanding of the mobility of the oils and, ultimately, production allocation. Best practices for thermally extracting hydrocarbons from drill cuttings, quality-controlling advanced mud gas data, and interpretive processes together with the entire workflow followed will also be elaborated. The analysis has the objectives of establishing results to support completion decisions through understanding reservoir quality, reservoir fluid communication, and compartmentalization specific to the basin studied. The petrophysical reservoir properties such as hydrocarbons in place, mobility of the oils, porosity, permeability, fracture intensity, geomechanical properties (brittle vs. ductile), and production allocation will be tied in to geochemical analyses to this extent. The focal point of the work is ascertaining and characterizing both the reservoir properties using a number of integrated analytical techniques on DST oil samples of 12 offset wells and rock cuttings, as well as petrophysical logs and advanced mud gas data. The concepts, tools, and methods that have been demonstrated for evaluating crude oils, natural gases, and petrophysical characteristics of the rocks are applicable to many problems in petroleum production and field development as well as exploration efforts.

Digital Transformation of Production Allocation and Management for Oil and Gas Field

Output is the core index of oil and gas enterprises, and the management of output is very important to the operation of oil and gas enterprises. Each year, oil and gas companies will develop a production allocation plan according to well productivity. Under the guidance of the allocation plan, the annual production target would finally be achieved. In the digital transforming stage of development and production management of oil and gas fields, the traditional offline manual production allocation can no longer meet the needs of delicacy management. For this reason, based on the development and production management platform, a system of production allocation and management was established and deployed in an international oil and gas company. In this paper, through the information platform concept model, introduced the development and production management platform construction method. Based on the platform architecture, taking production allocation and management as an example, the system construction process is introduced from the aspects of business process splitting, system function design, data and software integration call, etc. Furthermore, through the integration of intelligent oil and gas project results based on the platform architecture, the integrated application of intelligent workflow to core business activities in the production allocation and management process is realized. The platform has been fully applied by a large natural gas production company. Through this platform, a management mode with "business standardization, process standardization, and execution standardization" was adopted to realize the comprehensive transformation of production allocation and management from the traditional mode to the digital one. The application of the platform shows that: the process of production allocation and management optimized in process-driven way is traceable and can form a business closed loop; through process reorganization and integrated application, the efficient business collaboration across specialities and departments has been achieved, improving the scientific decision-making ability and the level of business management;