Overview

Maps have been one of the most important human inventions for millennia, allowing humans to explain global geography and geology and to navigate the world. The oldest surviving maps include cave paintings and stone engravings, followed by maps produced in ancient Babylon, Greece, Rome, China, and India. In their simplest form, maps are two-dimensional constructions; however, since the time of classical Greece, maps have also been projected onto a three-dimensional sphere and nowadays even four-dimensional when the time variable also plays its role, as in simulations.

With the passage of time and technological advances, the making of maps has evolved and developed, reaching what they are today, quite precise representations of areas of interest, being able to be two-dimensional and three-dimensional, whose variety of themes range from geographical representations to properties present on the earth's surface such as minerals existing in a specific area.

In geology and related disciplines, the use of maps is essential from exploration to development and production. Speaking essentially of the oil and gas industry there are a variety of maps that are commonly used such as geological, isoproperties, reservoir qualities, surface facilities, etc... but very little about quantities and qualities of information maps. That is why this work has the purpose of developing a workflow that allows to demonstrate the effect of the quantity and quality of the data used in reservoir integrated studies, i.e: well logs, cores, and production reports, represented in certainty maps previously to reservoir studies through a practical workflow, reducing execution times.

Thanks to technological growth and its impact on reservoir studies, it is advisable to base the analysis of hydrocarbon prospects on more efficient workflows, optimizing results, reducing uncertainty, and eliminating delays.

The need to establish this type of workflow is based on cutting project execution times to make them more efficient, without sacrificing quality. There are tools that allow speeding up projects; However, these systems need constant revisions to allow optimization between existing digital platforms and multidisciplinary teams. That’s why the need to implement new methods that are more practical, fast, and efficient in order to satisfy the continuous demands of industry.

Frequently, the results of a geological or reservoir study are affected by the quantity and quality of the available information, regardless of the method used and the capacity of the professionals involved. Along with this idea, this research seeks to optimize the processes in the work chain for the search, delimitation and production of a reservoir, proposing the development of a workflow for the generation of certainty maps from the elaboration of information matrices that allow the selection of key wells on which a reservoir, geological or petrophysical model of optimum certainty can be based on. Having said that, the main task of this workflow is to design an optimized methodology to generate certainty maps considering the quality and quantity of the available data in order to reduce the execution time of the projects without affecting the quality of the results.

The available data is of public domain  from Volve Field in the North Sea, Norway. This field was selected due to its dimensions together with the fact that the information is freely accessible, facilitating its management and distribution. Regarding the general characteristics of this field, it is located in the central part of the North Sea, five kilometers north of the Sleipner Øst field. The depth of the water is 80 meters. Volve was discovered in 1993, and the Plan of Development and Operations (PDO) was approved in 2005. The field was developed with a jackup drilling and processing facility. Production started in 2008. This field produced oil from Middle Jurassic sandstone in the Hugin Formation. The reservoir is located at a depth of 2,700-3,100 meters. The western part of the structure is heavily faulted and communication across the faults is uncertain. Pressure support water injection was used for production. It was closed in 2016 and the facility was removed in 2018. The Volve field is a large 2x3 km structure with restricted rejection and forms as a result of salt movements and stretching during and immediately after reservoir deposition. It was dominated by the tides, which has resulted in a great lateral extension of the sandstone layers. A series of Triassic-Jurassic formations with sandy intervals are found throughout the North Sea, as seen in the lithostratigraphic column in figure 1. These units constitute important reservoirs and aquifers. Thick shale formations with good sealing capacity occur throughout the Jurassic and Cretaceous sequences.

A total of 24 wells were used to carry out this study. Below, in table 1, the wells, their original & Short names and their respective coordinates are shown.

Methodology

Scientific research is a methodical and systematic process aimed at solving scientific problems or questions through the production of new knowledge, which constitutes the solution or answer to such questions. Three types are recognized: exploratory, descriptive, and explanatory (Arias, F., 2016). Exploratory research is one that is carried out on an unknown or little-studied topic or objective, so its results constitute an approximate vision of said objective (Arias, F., 2016). Based on the above, and due to the fact that the certainty maps are created by the Inter-Rock technical group, it results in a topic that has been little studied. That is why this research would be of an exploratory type, since it is oriented towards designing a methodology for the construction of certainty maps, through the creation of a matrix made up of various categories of information as data from well logs, drilling cores, production data and technical reports. After a rigorous inventory, the proposed workflow consists of the following major activities:

1. Classification of the categories of information and amount of available data from which the certainty maps are generated.

2. Establish the certainty criteria per well, formation, or reservoir for which the corresponding certainty maps would be generated.

3. Determination of information quality parameters based on the categories of available data.

4. Design a matrix where weight values and ratings corresponding to each data item from each category can be assigned based on their quantity, quality, and the type and the objectives of each study. 

5. Generate certainty maps by well/formation/reservoir; from the total certainty matrix, based on the quantity and quality of available data.

6. Rank the wells based on the score obtained in the certainty matrix according to the applied criteria and areal distribution, in order to select the key wells for geological & petrophysical models in Integrated Reservoir Studies.

7. Document a workflow for the generation of certainty maps, using a weighted matrix of information categories. 

Determining the quality of the available data such as records, cores, production data, etc... comprises an important part in carrying out the inventory and the status of the data, in this segment, it must be identified if the quality is good, acceptable, or unacceptable.

Description of the main activities for the Certainty Maps workflow:

1. Classification of information categories from available data

The available data from the Volve field were validated, QC’d, studied and grouped into 3 large categories, which are: logs, cores and production data. Specialists and interpreters of Inter-Rock created a master table (Table II) to classify the available data within the three pre-selected categories.

For the core category, the core management protocol report provides the necessary support to manage reliability and credibility to the core data that is available, for this it is worth mentioning the main factors that affect the core data:

1. Sample extraction methods.

2. Alteration of wettability.

3. Clay damage

4. Porosity evaluation.

5. Pore volume compressibility

6. Laboratory handling & management.

7. Laboratory reporting requirements.

All of these factors already mentioned have a great weight on the quality of the core data, so, having a core management protocol report is very important; in its absence, great uncertainty is created regarding the reliability of the available information.

For the production category, it uses entirely the experience and knowledge that the interpreter has when analyzing the available data, considering whether the initial tests were properly performed, at what time in the life of the field the PVT analysis were done as well as the water sampling and physical-chemical analysis comply with protocols. 

4. Matrix Design and  weight qualification values for each type of data based on its quantity, quality, and the type and the objectives of each study

To create the matrix Excel program was used, starting from the already established categories, 4 different spreadsheets were created which would contain the information for logs, cores, production, and total well certainty.

Specifically for this work, for each data category, that is, logs, cores, and production, a weight is assigned according to the type of project being worked on, also in the Total Well Certainty sheet, in the column so called Total Certainty, percentage weight values are assigned to each of the 3 categories depending on the project, in such a way that the sum results in 100%. Additionally, for the purposes of this research, two types of projects were established, one for petrophysics and the other one for geosciences, using the data available from the Volve Field. These weights were assigned with the advisory of interpreters and experienced professionals from the consulting company Inter-Rock.

Either for the petrophysical or Geoscience project, the percentage values that each category represents for carrying out the total certainty calculation are shown in tables III and IV respectively. These weights or percentage values are considered variable or conveniently modifiable, depending on the nature of each project, always based on a multidisciplinary consensus.

5. Generate certainty maps by well, formation or reservoir based on the results obtained from the certainty matrix, depending on the quantity and quality of the available data

The Surfer 16 tool from “Golden Software” was used to generate the certainty maps. The aforementioned maps were prepared for each of the categories of information: Logs, Cores, Production as partial steps before total certainty maps are built either for the petrophysical and geological projects, after obtaining partial and final results of the certainty matrix. To load the data into the mapping software, the North and East bottom coordinates of each well were used, as these wells were offset. Additionally, a Z value was needed, which in this case was certainty. In this research, the population or universe of data is conceived as the space from which the sample has been extracted. Balestrini, (2006) stated that: The sample is a “representative subset of a universe or population.” In this sense, the sample of this project is made up of 24 wells from the Volve field, located in the North Sea. It was ensured that the selected wells had basic information, well logs, eventually cores and production reports.

For the purposes of this work, total certainty maps resulting from the two exercises carried out for both the petrophysical and geoscience projects were generated and  shown in figures 4 and 5. It is important to mention that certainty maps by category were also generated and discussed based on the quantity and quality of the data from records, cores and production reports available, which were somehow added and normalized to manage the total certainty maps. for each project.

It is observed that specific areas of petrophysical project certainty map, have good certainty toward the central-western and north-eastern areas of the field, this means that these areas have considerable amount of information as well as good quality. Furthermore, other smaller areas located toward the center and the northernmost area of the map show low certainty, that is, the quantity and quality of the data is low.

In the total certainty map of the Volve field for the geological project, it is observed a high percentage of certainty in the majority of the Volve field, highlighting specific wells located between the SW and NE zones, that is, in those zones the quantity and quality of the data is greater. On the other hand, there is a specific area with very low certainty, located toward the central-northern of the total certainty map, this means that this area has scarce data and/or its quality is low as well. 

6. Wells Ranking based on the score from resulting certainty matrix.

As mentioned before, this article based its case study developing the certainty maps methodology on two types of studies using the same database, a petrophysical and a geological study. Said that, a Hierarchy of the wells based on the score obtained in the certainty assessments was made based on correspondent criteria for both projects.

Regarding the petrophysical project, the values previously obtained for total well certainty, it was possible to highlight nine (9) key wells with a good certainty qualification (>40%), as well as the case of four (4) wells with extremely low certainty (<12%), which we can be seen in figure 6. It’s important to mention that, in any case and for this study, there is not a scientific criterion or a magic number under which a limit of “acceptable” or “unacceptable” certainty will be assigned. It all depends on available data, the nature and specific objectives of the project. 

In the case of the geoscience project, a ranking of the wells based on the certainty matrix was done. From previously geology study total well certainty assessment, 7 key wells were identified with acceptable certainty over a total of 24 wells. Figure 7.

7. Documentation of a detailed workflow for the generation of certainty maps, using a weighted matrix of information categories.

This work represents an exploratory research since it is carried out on an unknown or little studied topic or objective. The results obtained constitute an approximate vision of what a certainty map should be based on the stated objectives. Based on the above, and because the certainty map workflow is an original procedure created by Inter-Rock, it is an understudied topic. This is why the main objective of this research is the design of a methodology for generating certainty maps, through the creation of a matrix made up of various categories of information, well log data, drilling cores and production data. The results obtained have given rise to a workflow which has been documented and represented in figure 8, defining each of the steps to follow in the generation of the certainty maps.

Evidently, in this Certainty Map Generation procedure, it is possible to realize that this workflow is 100% compatible with machine learning. Artificial intelligence through machine learning could even, without any doubt, generate numerically the key wells from a certain cutoff of certainty, without the need to generate the maps; However, knowing where wells or reservoir areas are located with greater or lesser certainty is as important as the actual work of classifying wells or classifying deposits according to the best or worst areas with greater or lesser certainty and the better or worse quality of the information. That is why maps are essential to establish the location and the reasons of Certainty variations. In a project like this, geographical location definitely has an important weight.

It is definitely advisable to promote the implementation of certainty maps as a valuable diagnostic tool for the available data prior to the execution of integrated reservoir studies. This procedure will also be of great help as it will lead to improvements in planning to capture new and missing data. Obviously, the participation of experienced professionals in multidisciplinary teams would be pertinent for the purposes of assigning weights to the categories and subcategories of information in the corresponding matrices for the generation of certainty maps according to the nature of the study.

Finally, it would be undeniable that being able to select the true key wells for integrated reservoir studies would lead to solid results and more reliable models.

Acknowledgement

The authors would like to greatly appreciate the valuable collaboration of Dr. Alfredo Fernandez, a Senior Reservoir Geophysicist who knew how to facilitate and introduce the team to the huge and intricated dB of Volve Field.

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